Northeast Monsoon Rainfall Research Articles

Assessment of APCC models fidelity in simulating the Northeast monsoon rainfall variability over Southern Peninsular India

The fidelity of the eight Asia-Pacific Economic Cooperation (APEC) Climate Center (APCC) models in representing the inter-annual variability and decadal shift in the northeast monsoon (NEM; October–December) rainfall over Southern Peninsular India (SPI) is evaluated. The hindcast data is used for the period of 28 years from 1983 to 2010 based on September initial conditions. The observations showed a clear inter-annual and inter-decadal variability of NEM rainfall during the study period. The analysis suggests that most of the models exhibited poor skill in representing the inter-annual variability. Only APCC model rainfall is in phase with observed SPI rainfall variations on the inter-annual time scale. It is noticed from the observed NEM rainfall time series that the period 1990–1999 (first decade) displays an above-normal rainfall and the period 2000–2010 (second decade) displays a below normal rainfall over the SPI region. It is also evident from the observations that NEM rainfall for most of the years displayed negative anomalies in the second decade including El Nino and La Nina years, while in the first decade positive anomalies are noted, suggesting the presence of decadal variability in the NEM. Rainfall variations in most of the coupled models are in phase with the observations during the second decade but are out of phase during the first decade. As evidenced from the observations that the intensified deep convection over the Indo-western Pacific region results in too far southward movement of the intertropical convergence zone (ITCZ) during the second decade. The southward shift in the strong upper-level divergence associated with lower-level convergence over the south Indian Ocean caused negative rainfall anomalies over the SPI in this decade. Further, the difference between the second and first decade demonstrates that an anomalous anticyclonic circulation over the Indian subcontinent is accountable for the vigorous dry northerly flow towards the SPI region and the resultant decadal shift in the rainfall pattern. Though the southward shift in the rainfall and large-scale circulation patterns are mildly captured by some models from decade to decade, most of the models completely misrepresented it. This study suggests that the coupled models displayed a very limited skill not only in capturing the inter-annual variability but also in representing the decadal variability of NEM rainfall.

Variability and Trend Analysis of Rainfall Data of Shillong and Agartala Stations of North East India

This paper discusses the variability in rainfall and trend analysis of annual and seasonal rainfall time series of Shillong and Agartala stations located in the north-east region of India. Commonly used non-parametric statistical methods namely Mann-Kendall and Sen’s slope estimator was used to analyse the seasonal and annual rainfall time series. Statistical analysis showed less variation in annual and south-west monsoon rainfall for both Shillong and Agartala stations. In the total annual rainfall, the share of south-west (SW) monsoon, north-east (NE) monsoon, winter season and summer season rainfall was observed 64.60%, 13.22%, 1.40% and 20.80%, respectively for Shillong station of Meghalaya state. However, the contribution of SW monsoon, NE monsoon, winter season and summer season rainfall in the total annual rainfall was 59.59%, 9.55%, 1.14% and 29.72%, respectively for Agartala station of Tripura state. Non-significant increasing trends of rainfall was observed by 4.54 mm/year, 2.80 mm/year and 2.54 mm/year for annual, SW monsoon, and summer season, whereas, non-significant decreasing trends in rainfall for NE monsoon and winter season was observed with a magnitude of 1.83 mm/year and 1.63 mm/year for Shillong, Meghalaya during 1992 to 2017. Results also revealed that rainfall increased by 1.07 mm/year and 0.18 mm/year in SW monsoon and winter season whereas, rainfall decreased by 7.64 mm/year, 2.58 mm/year and 1.29 mm/year during annual, NE monsoon and summer season non-significantly during 1995 to 2019 in case of Agartala. The findings of present study will be useful for water management and crop planning in hill agriculture of Meghalaya and Tripura state of India.

Diversity in ENSO remote connection to northeast monsoon rainfall in observations and CMIP5 models

Diversifying impacts of El Nino/La Nina events on northeast monsoon (NEM; October to December) rainfall over southern peninsular India (SPI) are explored in observations and Coupled Model Inter-comparison Project Phase 5 (CMIP5) models. Analysis of observations suggests that about 30 to 40% of El Nino–Southern Oscillation (ENSO) events co-occurred with Indian Ocean Dipole (IOD) during the NEM season (October to December). It is found from the observations that approximately half of the pure El Nino events show above-normal rainfall and remaining show below-normal rainfall over the SPI region, indicating the diversifying effect of El Nino on NEM rainfall. In the case of pure La Nina events, below-normal NEM rainfall is seen in 86% of events and above-normal rainfall in the remaining 14% of events. All El Nino–positive IOD (La Nina–negative IOD) co-occurrence years have witnessed positive rainfall anomalies over the SPI region. The strength and position of cyclonic/anticyclonic circulation over the South China Sea associated with positive/negative moisture anomalies are mainly responsible for the differences in rainfall patterns over SPI during ENSO events. It is found that in CMIP5 models the diversity in SPI rainfall pattern is not just limited to only pure El Nino and La Nina cases but also prominent in ENSO-IOD co-concerning years. CMIP5 models displayed strong skewness towards negative rainfall over the SPI region as compared with the observations during pure El Nino events. This would certainly limit the CMIP5 models’ ability to accurately represent ENSO teleconnections to NEM rainfall over the SPI region.

Precursors of northeast monsoon rainfall variability during extreme epochs of the global warming era

AbstractThe smoothed time series of northeast monsoon rainfall over south peninsular (SP) India has revealed two extreme active epochs (1877–1887 and 2005–2015) and two extreme weak epochs (1899–1909 and 1980–1990) during 1871–2016. Only the recent two epochs 1980–1990 and 2005–2015 were chosen due to data constraints. For these two epochs, the distribution of zonal wind pattern at the 850 and 200 hPa levels, latent heat flux, vertical shear in the zonal wind between 850 and 200 hPa, sea surface temperature and outgoing long wave radiation (OLR) were studied. The vertical profile of zonal wind over the mean position of the subtropical westerly jet and the maximum wind reversal were also analysed. Further, the frequencies of dry days, little rainfall days (0–20 mm), moderate rainfall days (20–60 mm), heavy rainfall days (60–100 mm) and very heavy rainfall days (>100 mm) were evaluated. SP India has experienced active/weak monsoon conditions every one to two decades alternately. An active monsoon epoch shows a higher north–south temperature gradient over the Bay of Bengal than a weak monsoon epoch. An upper level subtropical westerly jet over north India, strong tropical easterlies in the lower troposphere and low vertical shear in the zonal wind over the Bay of Bengal were observed during the active epoch, which facilitates the transportation of good amounts of moisture to SP India. The low OLR values over SP India in the active monsoon epoch indicate more convective activity over that region. Enhanced rainfall activity over SP India in the active monsoon epoch is due to the enhanced frequency of very heavy, heavy, moderate and little rainfall events and the reduced frequency of dry days.

Assessment of rainfall-induced soil erosion on hillslope: a case study at the Guthrie Corridor Expressway, Malaysia

The effect of northeast monsoon rainfall to soil erosion on hillslope adjacent the Guthrie Corridor Expressway, Malaysia, is investigated by examining a relationship between vegetation covers and slope steepness. Five plot-scale study areas [i.e., NBNM, PDM, PDNM, NBM and natural dense microbe (NDM)] are marked on the hillslope with different percentage and type of vegetation densities. Experimental equipment is set up at those plots to collect rainwater and soil loss starting from November 2014 until March 2015 with twice collection per month. Based on the data collected, the effect of different vegetation densities associated to soil loss is examined. These are the conclusions that can be made based on this investigation: (1) the observed rainfall pattern shows that mostly the recorded rainfall depth is about 5 mm with 20 min duration of rainfall; (2) plot without vegetation cover (i.e., NBNM) yields greater soil loss with the maximum runoff, whereas the least is exhibited by the plot having NDM. Meanwhile, the rate of soil loss is found greater for the planted vegetation compared to the natural plant; (3) a positive relationship is found between runoff and slope steepness regardless of the vegetation cover types.

Performance evaluation of CORDEX-South Asia simulations and future projections of northeast monsoon rainfall over south peninsular India

The northeast monsoon (October–December; NEM) rainfall is a very important entity to about 250 million people residing in the South Peninsular India (SPI) region as it is their principle rainy season and contributes mostly to their annual rainfall. The aim of the study is to obtain the future projections of NEM rainfall over this region representing three different greenhouse gas emission scenarios (i.e., RCP 2.6, RCP 4.5 and RCP 8.5) for two future time slices, i.e., near (2020–2049) and far future (2070–2099) estimated from a set of high-resolution regional climate simulations performed under CORDEX-SA experiments. To achieve that, first, an assessment of ten CORDEX-SA regional climate model (RCM) simulations is done for NEM rainfall over SPI for present climate (1976–2005) against India Meteorological Department high resolution (0.25o × 0.25o) gridded rainfall analysis dataset. Then, the change in NEM rainfall over SPI in the near and far future is computed after applying standardized reconstruction technique to adjust the bias present in the models. The results suggest that most of the CORDEX-SA experiments are able to simulate the spatial distribution of NEM seasonal rainfall and its variability over SPI but there is an inability in capturing realistic magnitudes and the errors are more over the east and west coast where most of the rainfall occurs. The experiment with RCA4 driven by EC-EARTH global model and REMO2009 driven by MPI-ESM has a fairly lesser bias than the other models, whereas the bias is more in LMDZ-IITM-RegCM4. The experiments by CCAM models have very similar characteristics in representing the rainfall pattern. The standardized reconstruction bias correction technique was found to significantly improve the performance of the climate models in representing the climatological mean and inter-annual variability of (IAV) of NEM rainfall over SPI, but in case of categorical rainfall years, improvement is seen only in the normal rainfall years. In the future, for RCP 2.6, there is a rise in NEM rainfall in the first half of the twenty-first century, which is projected to decline after that; however, in the other two scenarios, the rainfall is projected to increase. It is also found that there may be lesser excess rainfall years and more deficit rainfall years in the RCP 4.5 and 8.5 scenarios in the near future, and no deficit rainfall years are projected in the far future in both these scenarios based on the present climate. It is also noticed that the variability in the NEM rainfall over this region may remarkably increase in all the three future scenarios, which will highly impact various water resources management sectors. Thus, this study is very useful in determining the effects on various sectors due to the variability in NEM rainfall over this region and for adapting to climate change using advanced technologies for a sustainable future.

Exploring the drought condition in Namakkal District, Tamilnadu, through standardized precipitation index

Drought has long been recognized as one of the major causes of human misery and being the natural disaster that annually claims the most victims. Droughts are recurring climatic events, which often hit everywhere, bringing significant water shortages, economic losses and adverse social consequences. Water scarcity can be said as the cause and effect of drought. It is not possible to avoid droughts. But drought preparedness can be developed and drought impacts can be managed. The levels of drought preparedness in countries of the region differ significantly. The success of both depends, amongst the others, on how well the droughts are defined and drought characteristics quantified. Hence, an attempt has been made in this study to identify the drought condition on rainfed namakkal district. Annual normal rainfall of Namakkal is found to vary from 478 to 860 mm with an average of 732 mm. Among the monsoons, Southwest monsoon (SWM) had higher amount of average rainfall followed by Northeast monsoon (NEM) rainfall. During SWM, except the locations Paramathy all other locations have dependable rainfall. During NEM, the locations Namakkal, Rasipuram and Paramathy had CV higher than 50 Per cent that are not dependable. Except this all other locations have dependable rainfall. Most of the locations had witnessed 1 to 6 moderate drought years in both the monsoons. The study based on SPI will be helpful for assessing the drought severity. Keywords: Rainfall; SWM; CV; Drought; Index

Streamflow Variability in Mahaweli River Basin of Sri Lanka during 1990–2014 and Its Possible Mechanisms

This study investigates the variation of seasonal streamflow and streamflow extremes in five catchments of the Mahaweli River Basin (MRB) Sri Lanka from 1990 to 2014, and the relationship between streamflow and seasonal rainfall in each catchment is then examined. Furthermore, the influence of Indian Ocean Dipole (IOD) and El Nino and Southern Oscillation (ENSO) on the seasonal rainfall and streamflow in the upper (UMRB) and lower reaches (LMRB) of MRB are explored. It’s found that the rainfall amount in southwest monsoon (SWM) season contributes 29.7% out of annual total rainfall in the UMRB, while the LMRB records 41% of the total rainfall during the northeast monsoon (NEM) season. The maximum streamflow of upper (lower) Mahaweli catchments is observed in the SWM (NEM) season. Catchments in the UMRB (LMRB) recorded strong interannual variability of seasonal overall flow (Q50), Maximum 10-day, and 30-day flows during the SWM (NEM) season. It’s further revealed that the catchment streamflow in the UMRB is closely correlated with the SWM rainfall in the interannual time scale, while streamflow of catchments in the LMRB is closely associated with the NEM rainfall. The effects of ENSO and IOD on streamflow are consistent with their impacts on rainfall for all catchments in MRB, with strong seasonal dependent. These suggested that the sea surface temperature anomalies in the both Indian Ocean and tropical Pacific Ocean are important factors affecting the streamflow variability in the MRB, especially during the SWM season.

Physical-empirical models for prediction of seasonal rainfall extremes of Peninsular Malaysia

Abstract Reliable prediction of rainfall extremes is vital for disaster management, particularly in the context of increasing rainfall extremes due to global climate change. Physical-empirical models have been developed in this study using three widely used Machine Learning (ML) methods namely, Support Vector Machines (SVM), Random Forests (RF), Bayesian Artificial Neural Networks (BANN) for the prediction of rainfall and rainfall related extremes during Northeast Monsoon (NEM) in Peninsular Malaysia from synoptic predictors. The gridded daily rainfall data of Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) was used to estimate four rainfall indices namely, rainfall amount, average rainfall intensity, days having >95-th percentile rainfall, and total number of dry days in Peninsular Malaysia during NEM for the period 1951–2015. The National Centers for Environmental Prediction (NCEP) reanalysis sea level pressure (SLP) data was used for the prediction of rainfall indices with different lead periods. The recursive feature elimination (RFE) method was used to select the SLP at different NCEP grid points which were found significantly correlated with NEM rainfall indices. The results showed superior performance of BANN among the ML models with normalised root mean square error of 0.04–0.14, Nash-Sutcliff Efficiency of 0.98–1.0, and modified agreement index of 0.97–0.99 and Kling-Gupta efficient index 0.65–0.96 for one-month lead period prediction. The 95% confidence interval (CI) band for BANN was found narrower than the other ML models. Almost all the forecasted values by BANN were also found with 95% CI, and therefore, the p-factor and the r-factor for BANN in predicting rainfall indices were found in the range of 0.95–1.0 and 0.25–0.49 respectively. Application of BANN in prediction of rainfall indices with higher lead time was also found excellent. The synoptic pattern revealed that SLP over the north of South China Sea is the major driver of NEM rainfall and rainfall extremes in Peninsular Malaysia.

Northeast monsoon rainfall variability over the southern Peninsular India associated with multiyear La Niña events

The present study examines the variability of Northeast Monsoon (NEM) rainfall over the southern Peninsular India (SPI) associated with multiyear-La Nina events using observations and Coupled Model Inter-comparison Project Phase 5 (CMIP5) models. The analysis is carried out for NEM season (October–December) of two successive La Nina years, referred to as the first and second year during the period 1900–2010. Observations show that despite noticeable weakening in the equatorial Pacific cooling from the first year to the second year, strong La Nina teleconnections and the rainfall deficiency over the SPI region remains the same in most of the multiyear-La Nina events (70%). In the first year, zonally protracted low level cyclonic circulation over the north Indian Ocean (NIO) region induces northwesterly wind anomalies over SPI region. Negative moisture anomalies corroborated by northwesterlies and subsidence cause deficient rainfall over this region. On the other hand, the western flank of NIO cyclonic circulation is pushed towards Indian longitudes in the second year, inducing dry northerlies over SPI region. Development of low level divergent flow over the western tropical Indian Ocean and eastward migration of convergence zone from Bay of Bengal are found to be responsible for the shift in circulation pattern. These anomalous circulations together with low moisture content are responsible for deficit NEM rainfall in the second year. Differences in circulation patterns noted in the first and second year are associated with changes in the La Nina related SST patterns over the equatorial Pacific and modulation of the upper/lower level convergence/divergence zones. Analysis reveals that most of the CMIP5 models have tendency to simulate excess rainfall over the SPI region (in 70–100% of multiyear-La Nina events) unlike in the observations (30% of events). The possible reasons for the simulation of such positive rainfall anomalies are explored in the present study.

Comparison between the active tropical cyclone seasons over the Arabian Sea and Bay of Bengal

AbstractClimatologically, tropical cyclone (TC) activity in the North Indian Ocean (NIO) is asymmetric between the Arabian Sea (AS) and Bay of Bengal (BoB) basin. For the 172 TCs formed over NIO during 1983–2015, only 56 formed over AS and the rest (116) over BoB. During the period, AS was very active in a few years (but with quiet BoB season), and the opposite occurred in some others. It is found that this contrast occurred mostly during the post‐monsoon season of October–December. The meteorological and climate factors that accounted for these contrasting AS and BoB TC seasons are analysed. While climate variability such as the El Niño Southern Oscillation and Indian Ocean Dipole have known influences to NIO TC activity, results reveal that no single climate mode can well explain the TC development concentrating on AS or BoB only. Instead, it is found that variability of the northeast monsoon is an important factor responsible for the difference between the two basins. Excess moisture is available over the AS due to anomalous low‐level flow from the equatorial IO in the years in which there are more TCs in that basin, and dryer condition is over the BoB. In these years, there is likely excess northeast monsoon rainfall. The relationship is opposite between post‐monsoon BoB TC activity and the northeast monsoon. Nevertheless, the anomalous flow during active AS TC seasons is similar to that occurs during positive Indian Ocean Dipole, and thus this climate variability may be responsible for redistributing the moisture content in the NIO.

Multiresolution Analysis of Rainfall Variability Using Discrete Wavelet Transforms

The understanding of the percentage departure in rainfall from average with respect to time is very important for agriculture, environment and economy of any region. The rainfall variability on basis of its average monthly record during the period from Jan. 2013 to Dec. 2017 (05 years) in Moradabad, Uttar Pradesh, India, is discussed. Approximations are low frequency and details are high frequency content of the signal and hence play important role in signal or data analysis. Approximations provide information about the trend of signal. The trend is its slowest part of the signal and represents the behavior of signal corresponding to greatest scale value. A peak in the details shows rapid change or fluctuation in the quantity of rainfall in that time period. Skewness is a measure of symmetry and more precisely, the lack of symmetry while Kurtosis is a measure of whether the data are peakedness or flatness relative to a normal distribution. There is slight significant decreasing trend for long term northeast monsoon rainfall over Moradabad region.

Teleconnection between Cold ENSO Phases and Seasonal Rainfall Over Sri Lanka: Case Study in Kotmale Catchment

Cold ENSO phase or La-Nina is the least considered atmospheric oscillation in the hydro-meteorological sector in Sri Lanka. Therefore, this study focused on understanding teleconnection between cold ENSO phases and the seasonal rainfall over Kotmale catchment. Daily rainfall data of 9meteorological stations were used to investigate behaviour of annual rainfall climatologies of the catchment. Daily mean inflow data of Kotmale reservoir for the duration of 1984 - 2012 was analysed to understand the trends of the reservoir inflow. Sea surface temperature values were extracted from the Japan Meteorological Agency to determine cold ENSO phase. Rainfall trend for each station and inflow trend of the reservoir both declined throughout the selected time duration. However the rate of decreasing trend changes with each station. Seasonal rainfall of all the stations showed negative correlation with mean sea surface temperature over Nino 3 region for December to September. Cold ENSO phases encounter prominent above-average seasonal rainfall during and the onset of South-West monsoon. Further, onset and during of North-East monsoon rainfall over the catchment was weakened due to the impact of cold ENSO phase over Nino 3 region. However, further studies are suggested to identify hidden opposite phenomenon observed during cold ENSO phases on 1964 and 1967 in Kotmale catchment, where all the stations experienced worst below-average seasonal rainfall.

The Northeast Winter Monsoon over the Indian Subcontinent and Southeast Asia: Evolution, Interannual Variability, and Model Simulations

AbstractThe northeast monsoon (NEM) brings the bulk of annual rainfall to southeastern peninsular India, Sri Lanka, and the neighboring Southeast Asian countries. This October–December monsoon is referred to as the winter monsoon in this region. In contrast, the southwest summer monsoon brings bountiful rainfall to the Indo-Gangetic Plain. The winter monsoon region is objectively demarcated from analysis of the timing of peak monthly rainfall. Because of the region’s complex terrain, in situ precipitation datasets are assessed using high-spatiotemporal-resolution Tropical Rainfall Measuring Mission (TRMM) rainfall estimates, prior to their use in monsoon evolution, variability, and trend analyses. The Global Precipitation Climatology Center’s in situ analysis showed the least bias from TRMM.El Niño–Southern Oscillation’s (ENSO) impact on NEM rainfall is shown to be significant, leading to stronger NEM rainfall over southeastern peninsular India and Sri Lanka but diminished rainfall over Thailand, Vietnam, and the Philippines. The impact varies subseasonally, being weak in October and strong in November. The positive anomalies over peninsular India are generated by anomalous anticyclonic flow centered over the Bay of Bengal, which is forced by an El Niño–related reduction in deep convection over the Maritime Continent.The historical twentieth-century climate simulations informing the Intergovernmental Panel on Climate Change’s Fifth Assessment (IPCC-AR5) show varied deficiencies in the NEM rainfall distribution and a markedly weaker (and often unrealistic) ENSO–NEM rainfall relationship.

Predictability assessment of northeast monsoon rainfall in India using sea surface temperature anomaly through statistical and machine learning techniques

AbstractThe socio‐economic growth of India is adversely affected by the abnormal meteorological phenomena of floods and droughts. Thus, rainfall prediction is highly desirable for livelihood and sustainability. In this study, northeast monsoon rainfall (NEMR) is predicted over the Indian peninsular region for the months of October, November, and December using a global sea surface temperature (SST) anomaly as a predictor by linear regression (LR), artificial neural network (ANN), and extreme learning machine (ELM) techniques. The predictions are made by LR, ANN, and ELM models for the period 1990–2016 using the training input (1871–1989) of different time series samples of global SST anomaly data collected from Hadley Centre SST data set (HadSST3). Principal component analysis was used for dimensionality reduction of the data sets, and its application substantially improved the predictive ability of the machine learning techniques. The performance of the PC‐ELM technique with the ensemble method (ESM 8–9) training window is found to be more accurate than the LR and ANN techniques and provides minimal error scores as per the statistical analysis. This study concludes that the global SST anomaly has the potential to be used as a predictor for northeast monsoon rainfall and useful for long‐range climatic projections.

Critical comparison of north east monsoon rainfall for different regions through analysis of means technique

Critical comparison of north east monsoon rainfall for different regions through analysis of means technique

The local and global climate forcings induced inhomogeneity of Indian rainfall

India is home for more than a billion people and its economy is largely based on agrarian society. Therefore, rainfall received not only decides its livelihood, but also influences its water security and economy. This situation warrants continuous surveillance and analysis of Indian rainfall. These kinds of studies would also help forecasters to better tune their models for accurate weather prediction. Here, we introduce a new method for estimating variability and trends in rainfall over different climate regions of India. The method based on multiple linear regression helps to assess contributions of different remote and local climate forcings to seasonal and regional inhomogeneity in rainfall. We show that the Indian Summer Monsoon Rainfall (ISMR) variability is governed by Eastern and Central Pacific El Niño Southern Oscillation, equatorial zonal winds, Atlantic zonal mode and surface temperatures of the Arabian Sea and Bay of Bengal, and the North East Monsoon Rainfall variability is controlled by the sea surface temperature of the North Atlantic and extratropial oceans. Also, our analyses reveal significant positive trends (0.43 mm/day/dec) in the North West for ISMR in the 1979–2017 period. This study cautions against the significant changes in Indian rainfall in a perspective of global climate change.

Combined effect of MJO, ENSO and IOD on the intraseasonal variability of northeast monsoon rainfall over south peninsular India

The present study has examined the combined effect of MJO, ENSO and IOD on the intraseasonal and interannual variability of northeast monsoon rainfall over south peninsular India. The study has revealed that the intraseasonal variation of daily rainfall over south peninsular India during NEM season is associated with various phases of eastward propagating MJO life cycle. Positive rainfall anomaly over south peninsular India and surrounding Indian Ocean (IO) is observed during the strong MJO phases 2, 3 and 4; and negative rainfall anomaly during the strong MJO phases 5,6,7,8 and 1. Above normal (below normal) convection over south peninsular India and suppressed convection over east Indian and West Pacific Ocean, high pressure (low pressure) anomaly over West Pacific Ocean, Positive (negative) SST anomalies over equatorial East and Central Pacific Ocean and easterly wind anomaly (westerly anomaly) over equatorial Indian Ocean are the observed features during the first three MJO (5, 6, 7) phases and all these features are observed in the excess (drought) NEMR composite. This suggests that a similar mode of physical mechanism is responsible for the intraseasonal and interannual variability of northeast monsoon rainfall. The number of days during the first three phases (last four phases) of MJO, where the enhanced convection and positive rainfall anomaly is over Indian Ocean (East Indian ocean and West Pacific Ocean), is more (less) during El Nino and IOD years and less during La Nina and NIOD years and vice versa. The observed excess (deficit) rainfall anomaly over west IO and south peninsular India and deficit (excess) rainfall anomaly over east IO including Bay of Bengal and West Pacific Ocean suggest that the more (less) number of first three phases during El Nino and IOD (La Nina and Negative IOD) is due to the interaction between eastward moving MJO and strong easterlies over equatorial IO present during El Nino and IOD years. This interaction would inhibit the development of long duration MJO and would result in short duration high frequency MJO type which confined over Indian Ocean and south peninsular India and hence make all the El Nino and IOD years to be excess rainfall years for NEM season.

Investigating the Teleconnection between Warm ENSO Phases and Seasonal Rainfall over Kotmale Catchment in Sri Lanka

Seasonal rainfall over Kotmale reservoir is changing at an alarming rate due to atmospheric oscillations taking place over Sri Lanka. Therefore, this study focused on the teleconnection between warm El-Nino Southern Oscillation (ENSO) phases and rainfall over the Kotmale catchment. Daily rainfall data obtained from 11 meteorological stations were used to identify the behaviour of the annual rainfall climatologies of the catchment. Inflow data of the Kotmale reservoir obtained for the period 1984 to 2012 were analysed to understand reservoir inflow trends. Sea surface temperatures were obtained from Japan Meteorological Agency to determine the warm El- Nino Southern Oscillation phase. The rainfall at the stations and the inflow to the reservoir have declined over the period selected. However, the rate of decrease has varied from station to station. Seasonal rainfall at all the stations considered between December and September showed a negative correlation with the mean sea surface temperature of the Nino 3 region. Warm El-Nino Southern Oscillation caused below average seasonal rainfall over the catchment between December and September. The northeast and southwest monsoon rainfall over the catchment has weakened because of warm El-Nino Southern Oscillation phase in the Nino 3 region. However, the effect has got reduced with the onset of monsoons.

Northeast monsoon variations during the Holocene inferred from palaeochannels and active channels of the Palar River basin, Southern Peninsular India

The present-day Palar River and its palaeochannel located in the Southern Peninsular India were investigated with a multidisciplinary approach. The main aim of the study was to reconstruct the palaeoenvironment history of the Palar River basin and to delineate the role of Holocene fluctuations that played a major role in the geomorphological evolution of the region since the Holocene period. The results obtained based on sedimentary facies analysis supported by elemental concentrations and optically stimulated luminescence (OSL) dates reveal distinct seven climatic phases since the past ~10 ka. Phase 1 signifies a very high precipitation as attested by the low CWI with high Rb/Sr ratio. Subsequent to Phase 1, a decreasing trend in the northeast monsoon rainfall (NEMR) is observed (Phase 2). Phase 3 (~4.83–3.59 ka) reflects a decrease in NEMR further supported by low Mn/Al, Mg/Al and Chemical Index of Alteration (CIA) values. Phase 4 (~3.59 ka) is marked by high sand flux, higher K/Al, Ti/Al, Rb/Sr and Ba/Sr ratios coupled with lower values of CaO/MgO, Mn/Al and Fe/Al indicating wetter conditions in the catchment area resulting in the intense weathering of the bedrocks caused owing to the increase in NEMR precipitation. Phase 5 (3.26–2.42 ka) reveals a decline in NEMR precipitation coupled with rapid upstream avulsion because of neotectonic activity that occurred in an intense dry phase. Phase 6 (~1.88–1.44 ka) is marked by an augment NEMR causing higher K/Al, Mg/Al, Ti/Al ratios, CIA and CWI values. Finally, Phase 7 (~1.44 ka–present) is marked by lowered elemental solubility and mobility reflecting short periods of weaker or deteriorated NEMR. The documented record of the Palar River and palaeochannels suggests Holocene NEMR variability in the study region and is synchronous with the various proxy records of NEMR-dominated regions, however, revealing an inverse coupling with southwest monsoon rainfall (SWMR) during the Holocene period.