Southwest Monsoon Months Research Articles

High‐intensity rainfall over northeast India: Spatial pattern, short‐term fluctuations and associated multiscale oscillations

AbstractNortheast India (NEI) receives most of its rainfall in the southwest monsoon (SWM) season. The region is known to have frequent and persistent rainfall events of high intensities and the region is vulnerable to potential high‐impact meteorological events. This study analyses observed daily rainfall data for the SWM months (JJAS) during 1991–2020 to better understand the climatology of high‐intensity rainfall (HIR) occurrences and their persistence. The agglomerative hierarchical cluster analysis has delineated four distinct clusters and Cramer's t test indicates no significant fluctuations at 5% significant level in the HIR events in these clusters. ERA‐5 reanalysis data have been used to find the moisture transport for synoptic‐scale (3–7 days), quasi‐bi‐weekly oscillations (10–20 days) and intraseasonal oscillations (30–60 days) for each cluster. Under positive synoptic‐scale phases, HIR in the clusters on southern latitudes of NEI occurs due to moisture incursion from the Bay of Bengal from southwesterlies at 850 hPa, and in the clusters on the northern latitudes, it is primarily due to westerlies. For, quasi‐bi‐weekly oscillations, westerlies at 850 hPa are favourable for moisture transport in most of the clusters during its positive phase. On the other hand, for positive phase of intraseasonal oscillations, westerlies at 850 hPa dominate the moisture transport in all the clusters. Also, most of the HIR events occur whenever Madden–Julian Oscillation (MJO) is in phase 1 and 2 with higher amplitude (RMM ≥1).

TEMPERATURE AND SALINITY CHARACTERISTICS IN THE SOUTHERN SOUTH CHINA SEA AND STRAIT OF MALACCA

Temperature and salinity characteristics in the southern South China Sea and Strait of Malacca are investigated using CTD data and the global ocean model HYCOM. CTD data were obtained from cruises taken in March 2015, March 2019, and July-August 2019. The results showed that the average reading of temperature and salinity in the Strait of Malacca during March 2015 was 28.60±0.708 °C and 32.61±1.01 psu, respectively. The average readings during March 2019 were 29.31±1.593 °C and 32.38±0.884 psu, respectively. The average temperature and salinity in the Strait of Malacca during the August 2019 cruise were 29.63±0.701 °C and 32.52±0.553 psu, respectively. Meanwhile, in the southern South China Sea, the average readings in July 2019 were 28.98±0.310 °C and 33.07±0.126 psu and in August 2019 were 27.94±1.01 °C and 33.36±0.363 psu. Seasonal variations presented by the 15-years (1997-2012) HYCOM climatological model show that the sea surface temperature is warmer by approximately 1 - 2 °C during the southwest monsoon months (June-July-August) than during the northeast monsoon (December-January-February) in the southern South China Sea. The seasonal temperature variations in the Strait of Malacca are not significant except for the southern part. The sea surface salinity exhibits no clear seasonal cycle except for the coastal areas.

Total Column Water Vapor From INSAT-3D: Assessments With Ground-Based GNSS Receivers and GMI Datasets at Different Temporal Scales

The quality of the total column water vapor (TCWV) data retrieved from the Indian national satellite (INSAT) system series (INSAT-3D) and its variation at different temporal scales have been evaluated. The reference TCWV dataset is obtained from four ground-based global navigation satellite system (GNSS) receivers and over the entire Indian subcontinent from a global precipitation measurement (GPM) microwave imager (GMI) that uses global analysis (GANAL) model data. TCWV comparison of INSAT-3D, GPM-GMI with GNSS show higher correlations for GPM-GMI than INSAT-3D at all temporal scales. Though GMI can reproduce observed TCWV variations better than the INSAT-3D, the large biases of both the data sets indicate errors in the magnitude. Seasonal and monthly comparisons at two locations in the southeast peninsular India region show large correlations and small bias in the northeast and small correlations and large biases in southwest monsoon months. Southeast peninsular India receives a significant amount of rainfall in the northeast monsoon, and large TCWV correlations indicate both the algorithms removing cloud pixels with high accuracy. Therefore, the errors in the TCWV are attributed to the estimated radiances at different spectral channels. The spatiotemporal variations of TCWV correlations and bias of INSAT-3D indicate the need for improving the data quality by validating the estimated radiances at different spectral channels and, in turn, the retrieved TCWV over various regions at different temporal scales.

Spatial and temporal trends in high resolution gridded rainfall data over India

A high resolution (0.25°×0.25°) daily gridded dataset was analysed to study the spatial and temporal trend in various regions of India during the period of 1901–2013. The non-parametric Mann–Kendall (MK) test has been applied to the time series (1901–2013) rainfall data in order to detect the trends for both rainfall depth and number of rainy days. Sen slope estimator test was also used to find out the magnitude of the trend. In addition, Pettitt–Mann–Whitney (PMW) test was employed so as to determine the probable change year. The results of trend analysis of rainfall depth showed maximum number of grid points having increasing trend in summer months, while the dry months showed higher grid points with significant decreasing trend. Jammu and Kashmir, in particular, was found to have increasing trend in all months for all three levels of significances, i.e., 1%, 5%, and 10%, while NE (northeastern) region continuously reported significant decreasing trends. The annual trend analysis of the 30-year moving window of rainfall depth showed higher number of grid points with significant increasing trend during 1901–1950, decreasing trend during 1931–1980, and increasing trend again during 1961–2013. The PMW test for the rainfall depth and number of rainy days for 1901–2010 showed 1961 and 1974 as the most probable change point years with about 339 and 284 grid points agreeing upon it, respectively. The maximum increasing significant trends in rainfall was observed during south-west monsoon months. Recent years also reported an increase in rainfall intensity leading to probable increase of extreme events like floods and droughts.

Value Chain Analysis of Pen Shell (Baloko) in the Province of Sorsogon, Philippines

Sorsogon Bay is home to the pen shell (Atrina pectinata), locally known as Baloko. This study was designed to assess the existing value chains of pen shell and identify areas for improvement. The sites covered were the municipalities along Sorsogon Bay in the province of Sorsogon, Philippines. It employed the tracer methodology where only the processors and fisherfolks connected to the traders were selected as respondents of the study. Primary data were gathered through semi-structured questionnaires. Secondary data were used to establish a good understanding of the pen shell industry in the areas of the study. Results show that the adductor muscle or tinga is a substitute for scallops, thus, an export product. The other parts of pen shell or rambit are also of high demand. The highest volume of pen shell catch occur during October to April during the northeast monsoon (amihan) and gradually decline from May to September during the southwest monsoon (habagat) months. The value chain maps reflect the whole meat and semi-processed value chains, the two distinct marketing practices traced in the pen shell industry. The actors in the two value chains are the fisherfolks, processors, traders, and exporters. The enablers are the fisherfolks’ organization, local government unit (LGU), Bureau of Fisheries and Aquatic Resources (BFAR), City Fisheries and Aquatic Resources Management Council (CFARMC), microfinance institutions, Department of Trade and Industry (DTI), and Phil Export. There is uneven distribution of value added in both chains. More value is created and captured by the processors while the fisherfolks have negative gains. The value-added captured by the processors and traders are higher in semi-processed practice. There is the need to focus on the supply of pen shell, the effects of pollution of Sorsogon Bay, market information, technology to preserve the quality of products, industry association, and basic researches on pen shell under Sorsogon Bay condition.

Value Chain Analysis of Carpet Shell (Baduy) in the Province of Sorsogon, Philippines

The study was designed to assess the value chains of carpet shell and identify areas for improvement. The sites covered were the municipalities along Sorsogon Bay, in the province of Sorsogon, Philippines. It employed the tracer methodology. Only the traders and fisherfolks connected to the concessionaires and exporters were selected as respondents. Primary data were gathered through semi-structured questionnaires. Secondary data were used to establish a good understanding of the carpet shell industry. The highest volume of carpet shell catch occurred during December to April during the northeast monsoon (Amihan) and gradually declined from May to November during the southwest monsoon (Habagat) months. The Value Chain Maps reflected the fresh carpet for local market and for export market value chains, the two distinct marketing practices traced in the carpet shell industry. The actors in the two Value Chains are the fisherfolks, traders, concessionaires and exporters. The enablers are the fisherfolks’ organization, local government units (LGUs), Bureau of Fisheries and Aquatic Resources (BFAR), City Fisheries and Aquatic Resources Management Council (CFARMC), and microfinance institutions. More value is created and captured by the traders while the fisherfolks have least gains. The value-added captured by the traders were higher in fresh carpet shells for the local market than the export market. The areas of improvement will provide solutions to the problems on the supply of carpet shell, pollution of Sorsogon Bay, market information, technology to preserve the quality of products, industry association, and basic researches on carpet shell under Sorsogon Bay condition.

Circulation patterns in a shallow tropical reservoir: Observations and modeling

The diurnal circulation pattern is deduced in Kranji Reservoir, a shallow, elongated tropical reservoir in Singapore via field observations and results from the 3-D Estuary, Lake, and Coastal Ocean Model (ELCOM) model for the month of July 2012 which is during Singapore’s Southwest Monsoon season. Detailed comparisons of the modeled temperature and velocity fields with field measurements during a dry period of July 21–26 2012 without rainfall or inflow events are presented in terms of point comparisons, longitudinal profiles and cross-reservoir transverse velocity profile, thus providing a good representation of the flow field. Both observation and modeling show that the diurnal circulation pattern is driven by wind and by temperature gradients due to upwelling which depend on the time of the day. There is a daytime circulation pattern characterized by one large loop along the main channel, and a nighttime circulation characterized by two loops: one large loop between the reservoir dam and a location K1 (2500 m upstream from the dam where inflow tributary flows merge), and one small loop between K1 and the tributaries. These circulation patterns are consistent with the observed horizontal distribution of chlorophyll a during the Southwest Monsoon months over years 2008–2012. High chlorophyll a concentration occurs near the dam as expected due to downwelling within the large circulation loop and also close to the tributaries due to the nutrient from the catchments being trapped within the smaller loop. These results demonstrate the contributing effect of hydrodynamic flow on the biomass distribution that can occur in shallow tropical systems and which affects the diurnal and seasonal variation of biomass for such systems.

Precipitation Prediction for South West Monsoon Over Karnataka using Supervised Learning Technique

Weather forecasting is a major field of study in the area of Meteorology. Data Scientists, meteorologists and weather forecasters are implementing the experimentation of weather forecasting base on numerical and statistical methods. Traditional models used the fluid and thermal dynamic strategies for grid-point time series prediction based on few inherited constraints, such as the adoption of incomplete boundary rules, model assumptions and numerical instabilities. The nominated work is focused on finding the south west monsoon months’ precipitation patterns over the specific stations of Karnataka State. A multi-dimensional data framework for climate database with implementation online based data analysis has been developed. This works is carried out on the basis of monsoons that have prevailed during a year for the past 10 years. The proposed model emphasis the implementation of the association rules which has been extracted by the supervised classifier approach of data mining algorithms. The data mining technique of association rules emphasis the occurrence of the precipitation and will be helpful to take decisions in advance to the day to day operations in business, agriculture, water management and etc.

An Experiment in Weather Prediction for North East and South West Monsoon Over Chennai

There is a growing demand for spot specific forecast. Presently this has to be extracted from the regional forecast based on synoptic models. Synoptic models require input from various observatories of regions or the country and the central analysis centre is required for generating the synoptic charts. But recently the authors have established the potential of local data alone as a continuous time scale for use in effective local forecast using data mining techniques. Following the same association rule mining and classifier approach is tried for the forecast of wet and dog days on North East Monsoon and South West Monsoon months for the Chennai region with Latitude 13°11' N and Longitude 80°11' E, a coastal station over Bay of Bengal in South India and results are presented.

Association Rule Mining for South West Monsoon Rainfall Prediction and Estimation over Mumbai Station

Rainfall is important for agricultural yield and hence early prediction is required. It has a vital role in the improving the economy of a country. Accurate and timely weather prediction for rainfall forecasting has been one of the most challenging problems around the world as it changes the physical characteristics of the hydrologic system. Rainfall prediction model involves observation of weather data, deriving knowledge from it and implementing using computer models. The proposed work observed rainfall during south-west monsoon months of Mumbai (Latitude 19.0760°N / Longitude 72.8777°E) city. Predictive Apriori Algorithm was used to derive association rules for spot prediction, 24 hours ahead prediction and 48 hours ahead prediction, also to estimate a no rain day, moderate rain day and heavy rain day.

Climate change impacts on rainfall and temperature in sugarcane growing Upper Gangetic Plains of India

Assessment of variability in climate extremes is crucial for managing their aftermath on crops. Sugarcane (Saccharum officinarum L.), a major C4 crop, dominates the Upper Gangetic Plain (UGP) in India and is vulnerable to both direct and indirect effects of changes in temperature and rainfall. The present study was taken up to assess the weekly, monthly, seasonal, and annual trends of rainfall and temperature variability during the period 1956–2015 (60 years) for envisaging the probabilities of different levels of rainfall suitable for sugarcane in UGP in the present climate scenario. The analysis revealed that 87% of total annual rainfall was received during southwest monsoon months (June–September) while post-monsoon (October to February) and pre-monsoon months (March–May) accounted for only 9.4 and 3.6%, respectively. There was a decline in both monthly and annual normal rainfall during the period 1986–2015 as compared to 1956–1985, and an annual rainfall deficiency of 205.3 mm was recorded. Maximum monthly normal rainfall deficiencies of 52.8, 84.2, and 54.0 mm were recorded during the months of July, August, and September, respectively, while a minimum rainfall deficiency of 2.2 mm was observed in November. There was a decline by 196.3 mm in seasonal normal rainfall during June–September (kharif). The initial probability of a week going dry was higher (> 70%) from the 1st to the 25th week; however, standard meteorological weeks (SMW) 26 to 37 had more than 50% probability of going wet. The normal annual maximum temperature (Tmax) decreased by 0.4 °C while normal annual minimum temperatures (Tmin) increased by 0.21 °C. Analysis showed that there was an increase in frequency of drought from 1986 onwards in the zone and a monsoon rainfall deficit by about 21.25% during June–September which coincided with tillering and grand growth stage of sugarcane. The imposed drought during the growth and elongation phase is emerging as a major constraint in realizing high cane productivity in the zone. Strategies for mitigating the negative impacts of rainfall and temperature variability on sugarcane productivity through improvement in existing adaptation strategies are proposed.

UHF wind profiler observations of monsoon low-level jet (MLLJ) and its association with rainfall over a tropical Indian station

High resolution data of horizontal winds profiles (zonal and meridional) in the lower troposphere, derived from a UHF wind profiler at a tropical Indian station, Pune (18o 32’ N, 73o 51’ E, 559 masl) during a 3-yr period (June 2003-May 2006) has been utilized to study seasonal and intra-seasonal variability of winds. Winds display a systematic seasonal evolution with behavior opposite in phase in the two altitude regimes below and above a height of 4-5km. In the lower region, during the southwest monsoon months (June to September) winds are predominantly westerly with a peak in the 1.5-3.0km range indicating the occurrence of the monsoon low-level jet (MLLJ). Soon after September, winds in this height region change from westerly to easterly and these easterlies continue in winter months (December to February). Above a height of 4km, westerlies are observed during post-monsoon (October to November) and winter periods. The MLLJ is observed to be strong during normal/good monsoon years. On a day-to-day scale during southwest monsoon months, winds exhibit considerable intra-seasonal variability and periods of strong MLLJ seem to be associated with occurrence of spells of rainfall over the region.

Assessment of wave and solar energy potential along Western coast of India

Renewable energy is the need of the day to address energy crisis in the world. Renewable energy share in India is nearly 14% of the total installed capacity. Ocean energy does not contribute to this share at all. With a long coast line ocean energy has enormous potential of electricity generation in India especially for remote coastal areas which are still deprived of electricity. Although India is blessed with large amount of solar power, but during south west monsoon months, western coast of India experiences rainy season for around three to four months i.e. from June to September. Wave energy potential increases during monsoon months, which is evident from considerable increase in significant wave height and mean wave period. A hybrid arrangement with wave energy and solar energy generation using stand alone micro-grids can solve the problem of energy deficit and can also supply households of remote coastal areas of India that have no electricity.

Influence of Southeast Asian Haze episodes on high PM10 concentrations across Brunei Darussalam

Particulate matter (PM10) is the key indicator of air quality index in Brunei Darussalam and the principal pollutant for haze related episodes in Southeast Asia. This study examined the temporal and spatial distribution of PM10 base on a long-term monitoring data (2009–2014) in order to identify the emission sources and favorable meteorological conditions for high PM10 concentrations across the country. PM10 concentrations measured at the various locations differ significantly but the general temporal characteristics show clear patterns of seasonal variations across the country with the highest concentrations recorded during the southwest monsoon. The high PM10 values defined in the study were not evenly distributed over the years but occurred mostly within the southwest monsoon months of June to September. Further investigations with bivariate polar concentrations plots and k-means clustering demonstrated the significant influence of Southeast Asian regional biomass fires on the high PM10 concentrations recorded across the country. The results of the polar plots and cluster analyses were further confirmed by the evaluations with Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) backward air masses trajectories analysis and the Moderate Resolution Imaging Spectroradiometer (MODIS) fire records. Among the meteorological variables considered, temperature, rainfall and relative humidity were the most important meteorological variables that influence the concentration throughout the year. High PM10 values are associated with high temperatures and low amounts of rainfall and relative humidity. In addition, wind speed and direction also play significant role in the recorded high PM10 concentrations and were mainly responsible for its seasonality during the study period.

Evaluating the potential of rainfall product from Indian geostationary satellite for operational agromet advisory services in India

Satellite remote sensing technology is increasingly gaining recognition as an important source of operational agro meteorological services. Spatial daily rainfall product from geostationary satellite is one of the important data source for quick evaluation of suitability of sowing conditions and other economically relevant agricultural operations (irrigation, fertilizer applications, spraying etc.) by farmers as well as disaster (drought, flood) warning causing crop loss and also to derive weather derivatives for crop insurance. In view of that a study was taken up to explore the use of satellite based rainfall data at different temporal scales. Under the present study, comparison has been made between Kalpana-1 high resolution (0.25° x 0.25°) rainfall estimates for four south-west monsoon months (June-September) in two contrasting monsoon periods of 2008 (normal) and 2009 (drought) with in situ measurements andforecast (1° x 1°) at nine AMFUs (Agro-Meteorological Field Units) in different agro climatic zones.Initial analysis show less correlation and large root mean square error (RMSE) of Kalpana-1 daily rainfall estimates with measurements and forecast. However, correlation was found to increase significantly from 60 to 80% over weekly to fortnightly scale with concomitant decrease in RMSE.

Assessment of TRMM-based TMPA-3B42 and GSMaP precipitation products over India for the peak southwest monsoon season

Reliable information of rainfall and its variability at finer spatio-temporal scales over the Indian monsoon region is crucial for various applications in hydrology, meteorology, water resource management, and evaluation of high-resolution numerical model outputs. In this study, the Tropical Rainfall Measuring Mission (TRMM)-based high-resolution multisatellite rainfall products namely, TRMM Multisatellite Precipitation Analysis (TMPA)-3B42 and Global Satellite Mapping of Precipitation (GSMaP) are evaluated against recently released gauge-based India Meteorological Department (IMD) gridded data set. Both the research (delayed mode) and near real-time rainfall products of TMPA-3B42 (V7 and RT) and GSMaP (MVK and NRT) are evaluated over India at a daily scale for the peak southwest monsoon months of July–August. Two study periods (2000–2010 and 2009–2013) are used to accommodate the analyses based on data availability. Comparison of TMPA-3B42 (V7 and RT) and GSMaP-MVK with IMD gauge-based data for 2000–2010 shows that these data sets are able to represent large-scale monsoon rainfall spatial features, but are having region-specific biases. The interannual variability of monsoon rainfall averaged over India is also reasonably captured. However in terms of biases, TMPA-3B42RT overestimates rainfall by about 21% and GSMaP-MVK underestimates by about 22% at all-India scale. In terms of continuous skill metrics, TMPA-3B42V7 is closer to the IMD gauge-based observations possibly due to gauge adjustments. Categorical verification against gauge-based observations shows that the satellite-based data sets have difficulties in rainfall detection primarily over the northern Jammu & Kashmir regions, northeast India, and southern peninsular India. At subregional scale within India, satellite rainfall estimates show rather lower skill score in rainfall identification and larger uncertainty in rainfall estimation over the northeast India. Comparison of near real-time products of TMPA and GSMaP for July–August months of 2009–2013 shows that TMPA-3B42RT overestimates and GSMaP-NRT underestimates rainfall over most parts of India. Even though TMPA-3B42 (V7 and RT) and GSMaP-MVK rainfall data sets show similar diurnal variations over the Indian monsoon region, TMPA-3B42RT (GSMaP-MVK) shows larger (smaller) magnitude in diurnal cycle as compared to TMPA-3B42V7. Results from different skill metrics suggest that both research and near real-time versions of TMPA products can be used with relatively higher confidence as compared to GSMaP over the Indian region during peak monsoon period.

Formation, Growth and Variability of Sand Spit at Rushikulya River Mouth, South Odisha Coast, India

Sand spits are depositional landform and most active features near the coastal bays and inlets. The combine interactions between the wind, wave transformation, tidal variation, availability of sediment and river discharge decide the spit morphology, growth and orientation. The beaches around Rushikula river inlet is known as one of the largest rookeries of the olive ridley turtle. The spatial and temporal evolution of the sand spit, geomorphology changes and sediment distribution based on the data collected during 2005-2011 at different time intervals on the both sides of the inlet are assessed. Shoreline oscillation and geomorphology are monitored using real time global positioning system (RTK-GPS). The shoreline undergoes natural phases of erosion and deposition process, however, the entrapment of huge longshore sediment during southwest monsoon months near the river inlet triggers northerly progression of the sand spit and small temporary islands that are highly conducive for formation of nesting habitat. Sediment samples (n=210) collected at different transects representing fore, mid and backshore are analyzed to understand the role of grain size in erosion/ accretion process.

Diurnal and seasonal variation of mixing ratio and δ13C of air CO2 observed at an urban station Bangalore, India

We present here observations on diurnal and seasonal variation of mixing ratio and δ(13)C of air CO2, from an urban station-Bangalore (BLR), India, monitored between October 2008 and December 2011. On a diurnal scale, higher mixing ratio with depleted δ(13)C of air CO2 was found for the samples collected during early morning compared to the samples collected during late afternoon. On a seasonal scale, mixing ratio was found to be higher for dry summer months (April-May) and lower for southwest monsoon months (June-July). The maximum enrichment in δ(13)C of air CO2 (-8.04 ± 0.02‰) was seen in October, then δ(13)C started depleting and maximum depletion (-9.31 ± 0.07‰) was observed during dry summer months. Immediately after that an increasing trend in δ(13)C was monitored coincidental with the advancement of southwest monsoon months and maximum enrichment was seen again in October. Although a similar pattern in seasonal variation was observed for the three consecutive years, the dry summer months of 2011 captured distinctly lower amplitude in both the mixing ratio and δ(13)C of air CO2 compared to the dry summer months of 2009 and 2010. This was explained with reduced biomass burning and increased productivity associated with prominent La Nina condition. While compared with the observations from the nearest coastal and open ocean stations-Cabo de Rama (CRI) and Seychelles (SEY), BLR being located within an urban region captured higher amplitude of seasonal variation. The average δ(13)C value of the end member source CO2 was identified based on both diurnal and seasonal scale variation. The δ(13)C value of source CO2 (-24.9 ± 3‰) determined based on diurnal variation was found to differ drastically from the source value (-14.6 ± 0.7‰) identified based on seasonal scale variation. The source CO2 identified based on diurnal variation incorporated both early morning and late afternoon sample; whereas, the source CO2 identified based on seasonal variation included only afternoon samples. Thus, it is evident from the study that sampling timing is one of the important factors while characterizing the composition of end member source CO2 for a particular station. The difference in δ(13)C value of source CO2 obtained based on both diurnal and seasonal variation might be due to possible contribution from cement industry along with fossil fuel / biomass burning as predominant sources for the station along with differential meteorological conditions prevailed.

About the variability in thunderstorm and rainfall activity over India and its association with El Niño and La Niña

Thunderstorms are of much importance in tropics, as this region is considered to have central role in the convective overturn of the atmosphere and play an important role in rainfall activity. It is well known that El Nino and La Nina are well associated with significant climate anomalies at many places around the globe. Therefore, an attempt is made in this study to analyze variability in thunderstorm days and rainfall activity over Indian region and its association with El Nino and La Nina using data of thunderstorm day’s for 64 stations well distributed all over India for the period 1981–2005 (25 years). It is seen that thunderstorm activity is higher and much variable during pre-monsoon (MAM) and southwest monsoon (JJAS) than the rest of the year. Positive correlation coefficients (CCs) are seen between thunderstorms and rainfall except for the month of June during which the onset of the southwest monsoon sets over the country. CCs during winter months are highly correlated. Composite anomalies in thunderstorms during El Nino and La Nina years suggest that ENSO conditions altered the patterns of thunderstorm activity over the country. Positive anomalies are seen during pre-monsoon (MAM) and southwest monsoon months (JAS) during La Nina years. Opposite features are seen in southwest monsoon during El Nino periods, but El Nino favors thunderstorm activity during pre-monsoon months. There is a clear contrast between the role of ENSO during southwest monsoon and post-monsoon on thunderstorm activity over the country. Time series of thunderstorms and precipitation show strong association with similarities in their year-to-year variation over the country.

Black carbon aerosols in a tropical semi-urban coastal environment: Effects of boundary layer dynamics and long range transport

Regular measurements of Black Carbon (BC) aerosol mass concentration have been carried out since March 2011 at a tropical location (12.81°N, 80.03°E) adjoining the mega city, Chennai, on the east coast of India for the first time. As this region is influenced by both the South West and North East monsoons, the BC observations at this site assume importance in understanding the overall BC distribution over India. The data collected until August 2012 has been examined for the general and regionally distinctive features. Spectral absorption characteristics reveal that the BC is mainly from fossil fuel based emissions. The BC concentration shows significant diurnal variation only in the North East monsoon and winter seasons with night time concentration considerably higher than the day time concentration. In the other seasons the day–night contrast in BC is not significant. Seasonal variation is rather subdued with a broad maximum during the Northeast monsoon and winter months and a minimum during the southwest monsoon months. The observed diurnal and seasonal variations are examined in the light of local Atmospheric Boundary Layer dynamics and long range transport. For the first time, an inverse relationship has been established between BC and ABL height on a quantitative basis. A distinctive feature of the region is that in all the seasons transport pathways have long continental overpasses which could lead to the suppressed seasonal variation. It is found that the BC over this region shows distinct diurnal and seasonal features compared to those reported for other coastal and inland regions in India.