Sea-breeze-initiated rainfall over the east coast of India during the Indian southwest monsoon

Sea-breeze-initiated convection and precipitation have been investigated along the east coast of India during the Indian southwest monsoon season. Sea-breeze circulation was observed on approximately 70–80% of days during the summer months (June–August) along the Chennai coast. Average sea-breeze wind speeds are greater at rural locations than in the urban region of Chennai. Sea-breeze circulation was shown to be the dominant mechanism initiating rainfall during the Indian southwest monsoon season. Approximately 80% of the total rainfall observed during the southwest monsoon over Chennai is directly related to convection initiated by sea-breeze circulation.     

Active and break spells of the Indian summer monsoon

In this paper, we suggest criteria for the identification of active and break events of the Indian summer monsoon on the basis of recently derived high resolution daily gridded rainfall dataset over India (1951–2007). Active and break events are defined as periods during the peak monsoon months of July and August, in which the normalized anomaly of the rainfall over a critical area, called the monsoon core zone exceeds 1 or is less than −1.0 respectively, provided the criterion is satisfied for at least three consecutive days. We elucidate the major features of these events. We consider very briefly the relationship of the intraseasonal fluctuations between these events and the interannual variation of the summer monsoon rainfall.     

On the impacts of ENSO and Indian Ocean dipole events on sub-regional Indian summer monsoon rainfall

The relative impacts of the ENSO and Indian Ocean dipole (IOD) events on Indian summer (June–September) monsoon rainfall at sub-regional scales have been examined in this study. GISST datasets from 1958 to 1998, along with Willmott and Matsuura gridded rainfall data, all India summer monsoon rainfall data, and homogeneous and sub-regional Indian rainfall datasets were used. The spatial distribution of partial correlations between the IOD and summer rainfall over India indicates a significant impact on rainfall along the monsoon trough regions, parts of the southwest coastal regions of India, and also over Pakistan, Afghanistan, and Iran. ENSO events have a wider impact, although opposite in nature over the monsoon trough region to that of IOD events. The ENSO (IOD) index is negatively (positively) correlated (significant at the 95% confidence level from a two-tailed Student t-test) with summer monsoon rainfall over seven (four) of the eight homogeneous rainfall zones of India. During summer, ENSO events also cause drought over northern Sri Lanka, whereas the IOD events cause surplus rainfall in its south. On monthly scales, the ENSO and IOD events have significant impacts on many parts of India. In general, the magnitude of ENSO-related correlations is greater than those related to the IOD. The monthly-stratified IOD variability during each of the months from July to September has a significant impact on Indian summer monsoon rainfall variability over different parts of India, confirming that strong IOD events indeed affect the Indian summer monsoon.

Spatial monsoon variability with respect to NAO and SO

In this paper, the simultaneous effect of North Atlantic Oscillation (NAO) and Southern Oscillation (SO) on monsoon rainfall over different homogeneous regions/subdivisions of India is studied. The simultaneous effect of both NAO and SO on Indian summer monsoon rainfall (ISMR) is more important than their individual impact because both the oscillations exist simultaneously throughout the year. To represent the simultaneous impact of NAO and SO, an index called effective strength index (ESI) has been defined on the basis of monthly NAO and SO indices. The variation in the tendency of ESI from January through April has been analyzed and reveals that when this tendency is decreasing, then the ESI value throughout the monsoon season (June–September) of the year remains negative andvice versa. This study further suggests that during the negative phase of ESI tendency, almost all subdivisions of India show above-normal rainfall andvice versa. The correlation analysis indicates that the ESI-tendency is showing an inverse and statistically significant relationship with rainfall over 14 subdivisions of India. Area wise, about 50% of the total area of India shows statistically significant association. Moreover, the ESI-tendency shows a significant relationship with rainfall over north west India, west central India, central north east India, peninsular India and India as a whole. Thus, ESI-tendency can be used as a precursor for the prediction of Indian summer monsoon rainfall on a smaller spatial scale.     

Tropospheric biennial oscillation and south Asian summer monsoon rainfall in a coupled model

In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative) TBO is associated with La Niña (El Niño) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Niño-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysis suggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.     

Anomalous behaviour of the Indian summer monsoon 2009

The Indian subcontinent witnessed a severe monsoon drought in the year 2009. India as a whole received 77% of its long period average during summer monsoon season (1 June to 30 September) of 2009, which is the third highest deficient all India monsoon season rainfall year during the period 1901–2009. Therefore, an attempt is made in this paper to study the characteristic features of summer monsoon rainfall of 2009 over the country and to investigate some of the possible causes behind the anomalous behaviour of the monsoon.     

Unusual circulation pattern during Indian summer monsoon failure in July 2002 and June 2009

The circulation patterns over the Indian Ocean and the surrounding continents have been studied during June 2009 and July 2002 to explain the failure of Indian summer monsoon (ISM) rainfall. This study presents evidences that the failure of the ISM during these 2?months was probably due to the development of cyclonic circulation anomaly over the Western Asia and anticyclonic circulation anomalies downstream of Eastern Asia. These circulation anomalies were associated with the equatorward advection of cold air up to 10°N. This may be due to the equatorward intrusion of midlatitude Rossby waves. We hypothesize that the intrusion of midlatitude Rossby wave is responsible for breaking the east?Cwest circulation cell over the Indian region into two cells and weakening it. The weak east?Cwest cell reduces the strength of the easterly wind field usually present over the monsoonal region, thus reducing the cross-equatorial moisture transport into the Indian subcontinent and decreasing monsoon rainfall.     

Dominant impact of South Asian low heat on summer monsoon rainfall over Central India

Although previous literature have considered Southern Oscillation Index (SOI), Indian Dipole, and SST as the major teleconnection patterns to explain the variability of summer monsoon rainfall over India. South Asia low pressure and Indian Ocean high are the centers of action that dominates atmospheric circulations in Indian continent. This paper examines the possible impact of South Asian low pressure distribution on the variability of summer monsoon rainfall of India using centers of action approach. Our analysis demonstrates that the explanation of summer monsoon rainfall variability over Central India is improved significantly if the SOI is replaced by South Asian low heat. This contribution also explains the physical mechanisms to establish the relationships between the South Asian low heat and regional climate by examining composite maps of large-scale circulation fields using NCEP/NCAR Reanalysis data.     

Large-scale interannual variation of the summer monsoon over India and its empirical prediction

Large-scale interannual variability of the northern summer southwest monsoon over India is studied by examining its variation in the dry area during the period 1871–1984. On the mean summer monsoon rainfall (June to September total) chart the 800 mm isohyet divides the country into two nearly equal halves, named as dry area (monsoon rainfall less than 800 mm) and wet area (monsoon rainfall greater than 800 mm). The dry area/wet area shows large variations from one year to another, and is considered as an index for assessing the large-scale performance of the Indian summer monsoon. Statistical and fluctuation characteristics of the summer monsoon dry area (SMDA) are reported. To identify possible causes of variation in the Indian summer monsoon, the correlation between the summer monsoon dry area and eleven regional/global circulation parameters is examined. The northern hemisphere surface air temperature, zonal/hemispheric/global surface air and upper air temperatures, Southern Oscillation, Quasi-biennial oscillation of the equatorial lower stratosphere, April 500-mb ridge along 75°E over India, the Indian surface air temperature and the Bombay sea level pressure showed significant correlation. A new predictor parameter that is preceding year mean monsoon rainfall of a few selected stations over India has been suggested in the present study. The stations have been selected by applying the objective technique ‘selecting a subset of few gauges whose mean monsoon rainfall of the preceding year has shown the highest correlation coefficient (CC) with the SMDA’. Bankura (Gangetic West Bengal), Cuddalore (Tamil Nadu) and Anupgarh (West Rajasthan) entered the selection showing a CC of 0.724. Using a dependent sample of 1951–1980 a predictive model (multiple CC = 0.745) has also been developed for the SMDA with preceding year mean monsoon rainfall of the three selected stations and the sea level pressure tendency at Darwin from Jan–Feb to Mar–May as independent parameters.     

Spatio-temporal variability of summer monsoon rainfall over Orissa in relation to low pressure systems

The summer monsoon rainfall over Orissa occurs mostly due to low pressure systems (LPS) developing over the Bay of Bengal and moving along the monsoon trough. A study is hence undertaken to find out characteristic features of the relationship between LPS over different regions and rain-fall over Orissa during the summer monsoon season (June-September). For this purpose, rainfall and rainy days over 31 selected stations in Orissa and LPS days over Orissa and adjoining land and sea regions during different monsoon months and the season as a whole over a period of 20 years (1980-1999) are analysed. The principal objective of this study is to find out the role of LPS on spatial and temporal variability of summer monsoon rainfall over Orissa. The rainfall has been significantly less than normal over most parts of Orissa except the eastern side of Eastern Ghats during July and hence during the season as a whole due to a significantly less number of LPS days over northwest Bay in July over the period of 1980-1999. The seasonal rainfall shows higher interannual variation (increase in coefficient of variation by about 5%) during 1980-1999 than that during 1901-1990 over most parts of Orissa except northeast Orissa. Most parts of Orissa, especially the region extending from central part of coastal Orissa to western Orissa (central zone) and western side of the Eastern Ghats get more seasonal monsoon rainfall with the development and persistence of LPS over northwest Bay and their subsequent movement and persistence over Orissa. The north Orissa adjoining central zone also gets more seasonal rainfall with development and persistence of LPS over northwest Bay. While the seasonal rainfall over the western side of the Eastern Ghats is adversely affected due to increase in LPS days over west central Bay, Jharkhand and Bangladesh, that over the eastern side of the Eastern Ghats is adversely affected due to increase in LPS days over all the regions to the north of Orissa. There are significant decreasing trends in rainfall and number of rainy days over some parts of southwest Orissa during June and decreasing trends in rainy days over some parts of north interior Orissa and central part of coastal Orissa during July over the period of 1980-1999     

Influence of different land-surface processes on Indian summer monsoon circulation

The impact of different land-surface parameterisation schemes for the simulation of monsoon circulation during a normal monsoon year over India has been analysed. For this purpose, three land-surface parameterisation schemes, the NoaH, the Multi-layer soil model and the Pleim-Xiu were tested using the latest version of the regional model (MM5) of the Pennsylvania State University (PSU)/National Center for Atmospheric Research (NCAR) over the Indian summer monsoon region. With respect to different land-surface parameterisation schemes, latent and sensible heat fluxes and rainfall were estimated over the Indian region. The sensitivity of some monsoon features, such as Somali jet, tropical easterly jet and mean sea level pressure, is discussed. Although some features of the Indian summer monsoon, such as wind and mean sea level pressure, were fairly well-simulated by all three schemes, many differences were seen in the simulation of the typical characteristics of the Indian summer monsoon. It was noticed from the results that the features of the Indian summer monsoon, such as strength of the low-level westerly jet, the cross-equatorial flow and the tropical easterly jet were better simulated by NoaH compared with verification analysis than other land-surface schemes. It was also observed that the distribution of precipitation over India during the peak period of monsoon (July) was better represented with the use of the NoaH scheme than by other schemes.

Some characteristics of very heavy rainfall over Orissa during summer monsoon season

Orissa is one of the most flood prone states of India. The floods in Orissa mostly occur during monsoon season due to very heavy rainfall caused by synoptic scale monsoon disturbances. Hence a study is undertaken to find out the characteristic features of very heavy rainfall (24 hours rainfall ≥125 mm) over Orissa during summer monsoon season (June–September) by analysing 20 years (1980–1999) daily rainfall data of different stations in Orissa. The principal objective of this study is to find out the role of synoptic scale monsoon disturbances in spatial and temporal variability of very heavy rainfall over Orissa. Most of the very heavy rainfall events occur in July and August. The region, extending from central part of coastal Orissa in the southeast towards Sambalpur district in the northwest, experiences higher frequency and higher intensity of very heavy rainfall with less interannual variability. It is due to the fact that most of the causative synoptic disturbances like low pressure systems (LPS) develop over northwest (NW) Bay of Bengal with minimum interannual variation and the monsoon trough extends in west-northwesterly direction from the centre of the system. The very heavy rainfall occurs more frequently with less interannual variability on the western side of Eastern Ghat during all the months and the season except September. It occurs more frequently with less interannual variability on the eastern side of Eastern Ghat during September. The NW Bay followed by Gangetic West Bengal/Orissa is the most favourable region of LPS to cause very heavy rainfall over different parts of Orissa except eastern side of Eastern Ghat. The NW Bay and west central (WC) Bay are equally favourable regions of LPS to cause very heavy rainfall over eastern side of Eastern Ghat. The frequency of very heavy rainfall does not show any significant trend in recent years over Orissa except some places in north-east Orissa which exhibit significant rising trend in all the monsoon months and the season as a whole.     

Impact of vegetation on the simulation of seasonal monsoon rainfall over the Indian subcontinent using a regional model

The change in the type of vegetation fraction can induce major changes in the local effects such as local evaporation, surface radiation, etc., that in turn induces changes in the model simulated outputs. The present study deals with the effects of vegetation in climate modeling over the Indian region using the MM5 mesoscale model. The main objective of the present study is to investigate the impact of vegetation dataset derived from SPOT satellite by ISRO (Indian Space Research Organization) versus that of USGS (United States Geological Survey) vegetation dataset on the simulation of the Indian summer monsoon. The present study has been conducted for five monsoon seasons (1998–2002), giving emphasis over the two contrasting southwest monsoon seasons of 1998 (normal) and 2002 (deficient). The study reveals mixed results on the impact of vegetation datasets generated by ISRO and USGS on the simulations of the monsoon. Results indicate that the ISRO data has a positive impact on the simulations of the monsoon over northeastern India and along the western coast. The MM5-USGS has greater tendency of overestimation of rainfall. It has higher standard deviation indicating that it induces a dispersive effect on the rainfall simulation. Among the five years of study, it is seen that the RMSE of July and JJAS (June–July–August–September) for All India Rainfall is mostly lower for MM5-ISRO. Also, the bias of July and JJAS rainfall is mostly closer to unity for MM5-ISRO. The wind fields at 850 hPa and 200 hPa are also better simulated by MM5 using ISRO vegetation. The synoptic features like Somali jet and Tibetan anticyclone are simulated closer to the verification analysis by ISRO vegetation. The 2 m air temperature is also better simulated by ISRO vegetation over the northeastern India, showing greater spatial variability over the region. However, the JJAS total rainfall over north India and Deccan coast is better simulated using the USGS vegetation. Sensible heat flux over north-west India is also better simulated by MM5-USGS.     

The interannual variability of mid-latitude meridional circulation and its teleconnection with Indian monsoon activity

The statistical relationship between the summer monsoon rainfall over all India, northwest India and peninsular India, onset dates of monsoon and the index of mid latitude, (35° to 70°N) meridional circulation at 500 hPa level over different sectors and hemisphere based on 19 years (1971–1989) data, have been examined. The results indicate that (i) the summer monsoon rainfalls over all India, northwest India and peninsular India show a significant inverse relationship with the strength of meridional index during previous January over sector 45°W to 90°E. (ii) The summer monsoon rainfalls over all India and peninsular India show a significant inverse relationship with the strength of meridional index during previous December over sector 90°E to 160°E, (iii) The summer monsoon rainfall over northwest India shows a significant direct relationship with the meridional index during previous May over sector 160°E to 45°W. Significant negative relationships are also observed between the meridional circulation indices of previous October (sector 3 and 4), previous December (sectors 1, 3 and 4), previous winter season (sector 3 and 4) and the onset dates of summer monsoon over India. The meridional circulation index thus can have some possible use for long range forecasting of monsoon rainfall over all India, northwest India and peninsular India, as well as the onset dates of monsoon.     

Global temperature and monsoon activity

In this paper an attempt has been made to search a new parameter for the prediction of the Indian summer monsoon rainfall. For this purpose the relationship of the global surface-air temperature of four standard seasons viz., Winter (December-January-February), Spring (March-April-May), Summer (June-July-August), Autumn (September-October-November) with the Indian summer monsoon rainfall has been carried out. The same analysis is also carried out with surface-air temperature anomalies within the tropical belt (30°S to 30°N) and Indian summer monsoon rainfall. For the present study data for 30 years period from 1958 to 1988 have been used. The analysis reveals that there is a strong inverse relationship between the monsoon activity and the tropical belt temperature.     

Meteorological fields variability over the Indian seas in pre and summer monsoon months during extreme monsoon seasons

In this study, the possible linkage between summer monsoon rainfall over India and surface meteorological fields (basic fields and heat budget components) over monsoon region (30‡E-120‡E, 30‡S30‡N) during the pre-monsoon month of May and summer monsoon season (June to September) are examined. For this purpose, monthly surface meteorological fields anomaly are analyzed for 42 years (1958-1999) using reanalysis data of NCEP/NCAR (National Center for Environmental Prediction/National Center for Atmospheric Research). The statistical significance of the anomaly (difference) between the surplus and deficient monsoon years in the surface meteorological fields are also examined by Student’s t-test at 95% confidence level. Significant negative anomalies of mean sea level pressure are observed over India, Arabian Sea and Arabian Peninsular in the pre-monsoon month of May and monsoon season. Significant positive anomalies in the zonal and meridional wind (at 2 m) in the month of May are observed in the west Arabian Sea off Somali coast and for monsoon season it is in the central Arabian Sea that extends up to Somalia. Significant positive anomalies of the surface temperature and air temperature (at 2 m) in the month of May are observed over north India and adjoining Pakistan and Afghanistan region. During monsoon season this region is replaced by significant negative anomalies. In the month of May, significant positive anomalies of cloud amount are observed over Somali coast, north Bay of Bengal and adjoining West Bengal and Bangladesh. During monsoon season, cloud amount shows positive anomalies over NW India and north Arabian Sea. There is overall reduction in the incoming shortwave radiation flux during surplus monsoon years. A higher magnitude of latent heat flux is also found in surplus monsoon years for the month of May as well as the monsoon season. The significant positive anomaly of latent heat flux in May, observed over southwest Arabian Sea, may be considered as an advance indicator of the possible behavior of the subsequent monsoon season. The distribution of net heat flux is predominantly negative over eastern Arabian Sea, Bay of Bengal and Indian Ocean. Anomaly between the two extreme monsoon years in post 1980 (i.e., 1988 and 1987) shows that shortwave flux, latent heat flux and net heat flux indicate reversal in sign, particularly in south Indian Ocean. Variations of the heat budget components over four smaller sectors of Indian seas, namely Arabian Sea, Bay of Bengal and west Indian Ocean and east Indian Ocean show that a small sector of Arabian Sea is most dominant during May and other sectors showing reversal in sign of latent heat flux during monsoon season.     

Interannual variability of summer monsoon rainfall over Myanmar

Observed summer (May–October) rainfall in Myanmar for the period 1981–2010 was used to investigate the interannual variability of summer monsoon rainfall over Myanmar. Empirical orthogonal function, the sequential Mann-Kendall test, power spectrum analysis, and singular value decomposition (SVD) were deployed in the study. Results from spectral analysis showed that the variability of rainfall over Myanmar exhibits a 2- to 6-year cycle. An abrupt change in rainfall over the country was noted in 1992. There was a notable increasing rainfall trend from 1989. After the sudden change, the mean rainfall increased by 36.1 mm, compared with the mean rainfall before the sudden change, and was associated with a rise in temperature of about 0.2 °C. An increase in heavy rainfall days was observed from the early 1990s to 2010. IOD and ENSO play an important role in the interannual variability of the summer rainfall over Myanmar. The covariability between rainfall over Myanmar and Indian Ocean SST generally suggests that a positive IOD mode is associated with suppressed rainfall in the central and northern parts of Myanmar. During a negative IOD mode, nearly the whole Myanmar experiences enhanced rainfall, which is associated with devastating socioeconomic impacts. The covariability between the rainfall over Myanmar and the sea surface temperature in the Pacific Ocean in the first and second SVD modes was dominated by warming in the east and central Pacific—an El Niño-like pattern—resulting in dry conditions in central Myanmar.     

Trends in extreme rainfall over ecologically sensitive Western Ghats and coastal regions of Karnataka: an observational assessment

Rainfall is one of the pivotal climatic variables, which influence spatio-temporal patterns of water availability. In this study, we have attempted to understand the interannual long-term trend analysis of the daily rainfall events of ≥?2.5 mm and rainfall events of extreme threshold, over the Western Ghats and coastal region of Karnataka. High spatial resolution (0.25°?×?0.25°) daily gridded rainfall data set of Indian Meteorological Department was used for this study. Thirty-eight grid points in the study area was selected to analyze the daily precipitation for 113 years (1901–2013). Grid points were divided into two zones: low land (exposed to the sea and low elevated area/coastal region) and high land (interior from the sea and high elevated area/Western Ghats). The indices were selected from the list of climate change indices recommended by ETCCDI and are based on annual rainfall total (RR), yearly 1-day maximum rainfall, consecutive wet days (≥?2.5 mm), Simple Daily Intensity Index (SDII), annual frequency of very heavy rainfall (≥?100 mm), frequency of very heavy rainfall (≥?65–100 mm), moderate rainfall (≥?2.5–65 mm), frequency of medium rainfall (≥?40–65 mm), and frequency of low rainfall (≥?20–40 mm). Mann-Kendall test was applied to the nine rainfall indices, and Theil-Sen estimator perceived the nature and the magnitude of slope in rainfall indices. The results show contrasting trends in the extreme rainfall indices in low land and high land regions. The changes in daily rainfall events in the low land region primarily indicate statistically significant positive trends in the annual total rainfall, yearly 1-day maximum rainfall, SDII, frequency of very heavy rainfall, and heavy rainfall as well as medium rainfall events. Furthermore, the overall annual rainfall strongly correlated with all the rainfall indices in both regions, especially with indices that represent heavy rainfall events which is responsible for the total increase of rainfall.     

Analysis on MM5 predictions at Sriharikota during northeast monsoon 2008

The Indian northeast monsoon is inherently chaotic in nature as the rainfall realised in the peninsular India depends substantially on the formation and movement of low-pressure systems in central and southwest Bay of Bengal and on the convective activity which is mainly due to the moist north-easterlies from Bay of Bengal. The objective of this study is to analyse the performance of the PSU-NCAR Mesoscale Model Version 5 (MM5), for northeast monsoon 2008 that includes tropical cyclones – Rashmi, Khai-Muk and Nisha and convective events over Sriharikota region, the rocket launch centre. The impact of objective analysis system using radiosonde observations, surface observations and Kalpana-1 satellite derived Atmospheric Motion Wind Vectors (AMV) is also studied. The performance of the model is analysed by comparing the predicted parameters like mean sea level pressure (MSLP), intensity, track and rainfall with the observations. The results show that the model simulations could capture MSLP and intensity of all the cyclones reasonably well. The dependence of the movement of the system on the environmental flow is clearly observed in all the three cases. The vector displacement error and percentage of improvement is calculated to study the impact of objective data analysis on the movement and intensity of the cyclone.     

Prediction of monsoon rainfall with a nested grid mesoscale limited area model

At the India Meteorological Department (IMD), New Delhi, a 12-level limited area model with 100 km horizontal resolution has been in use for weather forecasting. The present study uses this model together with a higher horizontal resolution (50 km) and vertical resolution (16-levels) model to examine the impact of increased resolution to simulate mesoscale features of rainfall during monsoon disturbances. The model was run for 22 days in the month of August 1997 and one week in September 1997 during three monsoon depressions and one cyclonic storm in the Bay of Bengal. The model results are compared with observations. The study shows that the model can capture mesoscale convective organization associated with monsoon depression.