Bay Of Bengal Region Research Articles

Physical and optical properties of cirrus and subvisible cirrus clouds over Arabian sea and Bay of Bengal region

Cirrus clouds play a crucial role in regulating the Earth’s radiation budget, and this paper aims to contribute to a deeper understanding of their optical and geometrical properties over the Arabian Sea (AS) and Bay of Bengal (BoB) regions using CALIPSO data. Comprehensive statistics are derived, encompassing mean values of cirrus cloud top, base altitude, geometrical thickness, cloud optical depth, and temperature. Over the AS region, the mean values are 15.10 ± 1.50 km, 12.63 ± 1.75 km, 2.52 ± 1.37 km, 0.4 ± 0.58, and -62.30 ± 10.6 (°C), respectively. For the BoB region, the corresponding values are 15.43 ± 1.51 km, 12.72 ± 1.74 km, 2.71 ± 1.46 km, 0.49 ± 0.67, and -64.35 ± 10.7 (°C). A larger spread in optical depth and a higher frequency of occurrence for both cirrus and subvisible cirrus (SVC) clouds were observed over BoB compared to AS. Additionally, the study delves into SVC cloud characteristics, emphasizing their thinness and higher base altitudes compared to cirrus clouds. This comprehensive investigation contributes valuable insights into the distinctive properties of cirrus and SVC clouds in these regions, enhancing our knowledge of atmospheric processes and their implications for climate modelling and predictions.

Untangling the dynamics of heavy rainfall events (HRE) in the Northeast monsoon season and exploring its connection to the Indian Ocean warming and the Madden Julian Oscillation

Southeastern Peninsular India witnessed heavy rainfall events (HRE) during the recent El Nino year 2015 and La Nina year 2021 in November and early December. Both these events were associated with enhanced easterly wave activity and active Madden Julian Oscillation (MJO) over the Maritime continent. The MJO was on the fourth (MJO-4) phase for 15 and 17 days in November 2015 and 2021 respectively. A weakening in the positive correlation between El Nino and Northeast monsoon rainfall and a strengthening in the positive correlation between the MJO-4 days and HRE is observed in very recent years. This study revealed that the unequal changes in Sea Surface Temperature (SST) in the Indo-Pacific region i.e., warming over the eastern Indian Ocean (IO) and cooling over the western Pacific Ocean can be favourable for the increased occurrence of MJO-4 days as well as HRE over southern Peninsular India. The easterly wind anomalies towards the southern Bay of Bengal (BoB) and southeastern Peninsular India and westerly wind anomalies over the central equatorial Indian Ocean are significantly correlated with HRE in the recent epoch (2001−2021). Warming in eastern IO brings easterlies from the cool western Pacific and westerlies from the western IO, which helps the MJO to remain active over maritime continent and inhibits its further eastward propagation. The HREs in the recent epoch are associated with the low-pressure systems and cyclonic circulation over southern Peninsular India, in which moisture transport is from the Arabian Sea to Peninsular India. The HRE in the early epoch (1981–2000) is related to the anticyclonic circulation over BoB region and the moisture transport is from BoB and southeastern IO. A proposed mechanism for the HRE in the recent epoch is as follows. The SST gradient in the Indo-Pacific Ocean is conducive for the moistening of MJO-4 region and is favourable for the enhanced easterly wave activity and the formation of low-pressure systems, which get strengthened while moving towards southern Peninsular India due to the presence of strong equatorial westerlies over IO. These strengthened low pressure systems leads to strong ascending wind anomalies over southern Peninsular India and strong descending anomalies over Central IO and HREs over southern Peninsular India.

First record of the three-spined box crab, Arcania undecimspinosa De Haan, 1841 (Decapoda, Brachyura, Leucosiidae) from the Arabian Sea, with a key to the species of Arcania recorded from the Indian coast

Abstract A single specimen of the three-spined box crab, Arcania undecimspinosa De Haan, 1841, measuring 21.0 mm CW and 20.5 mm CL, is here documented for the first time from the Arabian Sea along the north-west coast of India. Previously, the species has been only reported from the Bay of Bengal region along the Indian coast. The present study provides a detailed taxonomic description of the species with high-resolution colour photographs and line drawings, along with a key to the species of the genus Arcania known from the Indian coast.

India and the Bay of Bengal region: ‘losing' the Cold War year’s advantage?

ABSTRACT This article discusses India’s perceived Sphere of Influence and examines New Delhi’s strategy in the Bay of Bengal (BoB) region during the Cold War (1947–1991) years. Then, this paper discusses how India had largely managed to keep the foreign powers away from the BoB region to maintain its influence and shape a favourable regional architecture. Finally, this paper briefly examines the changed strategic and political situation in the BoB region in present times.

Long‐term assessment of ERA5 reanalysis rainfall for lightning events over India observed by Tropical Rainfall Measurement Mission Lightning Imaging Sensor

AbstractThe ability of numerical weather prediction models to accurately predict extreme weather events, such as thunderstorms marked by heavy rainfall and lightning activities, has consistently been of great importance for human life. The objective of this study is to assess the long‐term reliability of the European Centre for Medium‐Range Weather Forecasts Reanalysis version 5 (ERA5) rainfall in comparison to the Indian gauge‐adjusted Global Satellite Mapping of Precipitation (GSMaP_ISRO) rainfall at the time of lightning flashes measured by the Lightning Imaging Sensor (LIS) onboard the Tropical Rainfall Measuring Mission satellite over the Indian region during the years 2001–2014. This analysis will provide valuable insights into the intricate relationship between lightning flashes and precipitation under various terrain conditions (low, mid, or high), across oceanic regions (Bay of Bengal, Arabian Sea), and during different monsoon phases (normal, active, or deficit). According to a prolonged examination of LIS data, April–June accounts for ~50% of the total flashes, with the largest number of flashes occurring over the Himalayan and the northeastern part of India. According to hourly GSMaP_ISRO rainfall, the most substantial lightning‐associated rainfall happens an hour prior to lightning flash (T − 1) and within three hours after (T + 3), indicating a robust correlation between heavy rainfall and lightning activity during this time frame. The rainfall in the ERA5 reanalysis misses the intensity as well as duration of the peak rainfall at the time of lightning flashes. Furthermore, the ERA5 reanalysis rainfall depicts under (over)‐estimation of rainfall in plain (orographic) regions. The underestimation of ERA5 rainfall is very pronounced over the Indian Ocean and Bay of Bengal regions, mainly between flash time (T) to two hours after the flash time (T + 2). The results indicate that there is a requirement for additional enhancements in the ERA5 reanalysis rainfall for lightning occurrences.

A single Prochlorococcus ecotype dominates the tropical Bay of Bengal with ultradian growth.

The Bay of Bengal (BoB) spans >2.2 million km2 in the northeastern Indian Ocean and is bordered by dense populations that depend upon its resources. Over recent decades, a shift from larger phytoplankton to picoplankton has been reported, yet the abundance, activity, and composition of primary producer communities are not well-characterized. We analysed the BoB regions during the summer monsoon. Prochlorococcus ranged up to 3.14 × 105 cells mL-1 in the surface mixed layer, averaging 1.74 ± 0.46 × 105 in the upper 10 m and consistently higher than Synechococcus and eukaryotic phytoplankton. V1-V2 rRNA gene amplicon analyses showed the High Light II (HLII) ecotype formed 98 ± 1% of Prochlorococcus amplicons in surface waters, comprising six oligotypes, with the dominant oligotype accounting for 65 ± 4% of HLII. Diel sampling of a coherent water mass demonstrated evening onset of cell division and rapid Prochlorococcus growth between 1.5 and 3.1 div day-1, based on cell cycle analysis, as confirmed by abundance-based estimates of 2.1 div day-1. Accumulation of Prochlorococcus produced by ultradian growth was restricted by high loss rates. Alongside prior Arabian Sea and tropical Atlantic rates, our results indicate Prochlorococcus growth rates should be reevaluated with greater attention to latitudinal zones and influences on contributions to global primary production.

Decision tree ensemble with Bayesian optimization to predict the spatial dynamics of chlorophyll-a concentration: A case study in Bay of Bengal

An accurate prediction of the spatial distribution of phytoplankton biomass, as represented by Chlorophyll-a (CHL-a) concentrations, is important for assessing ecological conditions in the marine environment. This study developed a hyperparameter-optimized decision tree-based machine learning (ML) models to predict the geographical distribution of marine phytoplankton CHL-a in the Bay of Bengal. To predict CHL-a over a large spatial extent, satellite-derived remotely sensed data of ocean color features (CHL-a, colored dissolved organic matter, photosynthetically active radiation, particulate organic carbon) and climatic factors (nighttime sea surface temperature, surface absorbed longwave radiation, sea level pressure) from 2003 to 2022 are used to train and test the models. Results obtained from this study have shown the highest concentrations of CHL-a occurred near the Bay's coastal belts and river estuaries. Analysis revealed that aside from photosynthetically active radiation, organic components exhibited a stronger positive relationship with CHL-a than climatic features, which are correlated negatively. Results showed the chosen decision tree methods to all possess higher R2 and lower root mean square error (RMSE) errors. Furthermore, XGBoost outperforms all other models in predicting the geographic distribution of CHL-a. To assess the model efficacy on seasonal basis, a best performing XGBoost model was validated in the Bay of Bengal region which has shown a good performance in predicting the spatial distribution of Chl-a as well as the pixel values during the summer, winter and monsoon seasons. This study provides the best ML model to researchers for predicting CHL-a in the Bay of Bengal. Further it helps to improve our knowledge of CHL-a spatial dynamics and assist in monitoring marine resources in the Bay of Bengal. It worth noting that the water quality in the Indian Ocean is very dynamic in nature, therefore, additional efforts are needed to test the efficacy of this study model over different seasons and spatial gradients.

Spatiotemporal Distribution and Evolution Characteristics of Water Traffic Accidents in Asia since the 21st Century

As an important mode of transportation for the global trade, waterborne transportation has become a priority option for import and export trade due to its large load capacity and relatively low cost. Meanwhile, shipping safety has been highly valued. By collecting technological water traffic accident data from the EM-DAT database, the spatiotemporal distribution and evolution characteristics were investigated in Asia since 2000. The methods of gravity center and standard deviation ellipse analysis were utilized to determine the spatial and data-related characteristics of water traffic accidents. Temporally, the results indicated that accidents occurred most frequently during the seasons of autumn and winter, leading to a significant number of casualties. Spatially, both South-eastern Asia and Southern Asia emerged as regions with a high frequency of water traffic accidents, particularly along the borders of Singapore, Malaysia, Indonesia, and the Bay of Bengal region. In addition, the Daniel trend test and R/S analysis were conducted to demonstrate the evolution trend of accidents across various regions and seasons. The present study provides guidance for improving marine shipping safety, emergency resource management, and relevant policy formulation.

Detection of materially coherent eddies from satellite altimetry in the Bay of Bengal

Mesoscale eddies are a well-recognized feature of the global oceans, being of dynamical relevance to various ocean processes and of significance to transport of various species. In the last few decades, advancements in satellite observations of the sea surface have revealed mesoscale and sub-mesoscale eddy features in many parts of the ocean. An objective definition and detection of eddies has, however, remained a challenge, thus resulting in unreliable estimates of eddy formation, evolution and dissipation. In this study, we present an implementation of a Lagrangian averaged vorticity deviation (LAVD) based method to detect and characterize eddies in the Bay of Bengal (BoB), a freshwater-dominated semi-enclosed basin in the northern Indian Ocean. Systematic sensitivity studies are performed to identify parameter values that result in robust eddy detection in the BoB, and finite-time coherence in material transport associated with the LAVD-based eddies is demonstrated. LAVD-based eddy detection is then used to statistically characterize the Sri Lanka dome (SLD) eddy, an annual mesoscale cyclonic eddy of dynamical and physical importance in the southern BoB. Analysing satellite-based ocean surface currents from 27 years (1993–2019) of data, the inter-annual variability in the SLD formation, its spatio-temporal evolution and dissipation are elucidated. On an average, SLD has a lifetime of 15 weeks and a maximum area of 5 square degrees, with the longest lifetime of 38 weeks in 1996 and a maximum area of 12 square degrees in 1998. Long-lived SLDs are shown to spatially excurse into the BoB, potentially influencing large-scale transport of physical and biogeochemical properties. A potential correlation between large SLD lifetime and large variations in the monthly evolution of Dipole Mode Index and NINO3.4 is highlighted. An SSH-based Eulerian eddy detection method is also implemented to understand its efficacy in identifying materially coherent eddies in the BoB region. The paper concludes with a summary of our results, and a brief discussion of potential applications of LAVD-based eddy detection in the northern Indian Ocean.

Indian merchants abroad: Integrating the Indian ocean world during the early first millennium CE

AbstractWith the rise of post-colonialism during the latter part of the twentieth century, more focus has been given to non-western perspectives (the so-called nativist turn). In the case of Indian Ocean trade during the early first millennium CE, the view that ‘Roman’ merchants and sailors were the near-exclusive movers of goods, who were also (indirectly) responsible for commercial developments within South Asia, has largely fallen into abeyance. Rightly, the agency of those in South Asia has been acknowledged. The present article goes beyond this basic premise and considers how we can assess evidence demonstrating the role played by sailors and merchants from South Asia. In particular, it is suggested these merchants and sailors played an important role in connecting the Arabian Sea and Bay of Bengal regions.

Spatio-temporal patterns of the multi-day fishing in the Indian Ocean off Sri Lanka, and their importance for fisheries monitoring, control and surveillance

In the present study, an attempt was made to investigate temporal and spatial patterns of multi-day fishing in the Indian Ocean off Sri Lanka to elucidate how such patterns related to fishing methods of multi-day fishing vessels targeting different pelagic fish species. In the analysis, 269,564 fishing operations from 37,349 fishing trips of multi-day fishing vessels during 2019 and 2020 were used. Based on the standardized fishing effort of the three major fishing methods (i.e., longlining, drift gillnetting and ring netting), species-wise catch per unit effort (CPUE) was determined for each fishing operation.The CPUE values of the three fishing methods were grouped for fishing locations in three major basins of the Indian Ocean, and according to three monsoonal seasons having varying influences of cyclones. Accordingly, 269,564 fishing operations were summarized into 77 datasets during the study period. The mean CPUE values (kg per fishing operation) were 257.3 for longlining, 163.3 for drift gillnetting and 1642.7 for ring netting. The patterns of the data matrix were investigated using the self-organizing map routine of the Artificial Neural Network. Accordingly, based on the occurrence of target species, data were classified into six clusters from which spatio-temporal patterns of fishing operations could be visualized. Ring netting was predominantly concentrated in the equatorial region and to a lesser extent in the Bay of Bengal region, with a temporal occurrence during all three seasons. Longline fishing was also predominant in the equatorial Indian Ocean region with the majority registered in the non-cyclone period. Most drift gillnet fishing operations were concentrated in the equatorial region and the Arabian Sea region, especially during the northern Indian Ocean cyclone period. These results would provide important pieces of information for the management of pelagic fish species through monitoring, control and surveillance (MCS) of the fishery.

Latent heat flux variability over the tropical Indian Ocean

AbstractThe seasonal evolution and interannual variability of latent heat flux (LHF) over the tropical Indian Ocean (TIO) region is examined for the period 1980–2019. The seasonal distribution of LHF is dominated by the winter pattern of each hemisphere in the TIO. Climatologically high LHF is mostly confined to the Arabian Sea and Bay of Bengal regions in the north Indian Ocean and the zonal belt between 10oS and 25oS in the south Indian Ocean. Warm and cold phases of El‐Niño Southern Oscillation, Indian Ocean Dipole (IOD), and their co‐occurrence events leave distinct LHF signatures over the TIO. The LHF anomalies during these events are more profound than pure events with enhanced latent heat loss when the La Niña and negative IOD events coincide. The LHF anomalies associated with the wind‐evaporation‐SST feedback is prominent when positive IOD co‐occur with the El‐Niño event. Both the vertical humidity gradient and wind speed changes play substantial roles in driving LHF anomalies during the co‐occurring events of NIOD and La Niña.

Assessing the performance of SWAN model for wave simulations in the Bay of Bengal

This study aims to comparatively evaluate two reanalysis wind fields, simulate waves driven by CFSv2 and ERA5, and test the simulation performance of the ST6 source term package of the SWAN model in the Bay of Bengal (BOB). A nested model using the third-generation numerical wave model SWAN is established from the Indian Ocean to the BOB, and the model calibration is adjusted based on various factors, including the driving wind field, input source function, physical parameters, and more. The importance of selecting appropriate input-dissipation parameterizations is stressed, as the ST6 source term package is better suited for BOB wave simulations, improving the modeling of wind input and swell dissipation compared to the KOMEN source function. There is a strong correlation between the wind field data from ERA5 and CFSv2 and the satellite altimeter wind speed data, with ERA5 showing superior performance. When the calibrated ST6 parameter values are combined with the ERA5 wind field, the SWAN model achieves a significant level of simulation accuracy, comparable to, or possibly slightly better than, that of the ECMWF WAM model for the specific application considered. The results offer valuable insights for improving the accuracy of wave forecasting models in the BOB region, with important implications for oceanography, fisheries, and disaster management.

Navigating the troubled waters: ‘maritimization' of Bangladesh’s foreign policy

ABSTRACT Bangladesh, a littoral state of Bay of Bengal, has historically played a marginal role in regional and global politics. Despite being a maritime nation, the maritime considerations have been absent in the country’s foreign policy formulation process. The article argues that the resolution of its maritime disputes with its neighbours has placed ‘maritime considerations’ in the heart of its foreign policy and the country has moved away from ‘land-centric’ regionalism to a more ‘maritime-centric’ regionalism over the past decade. This transformative shift represents the country’s ambition to become a ‘middle power’ in regional and global affairs with a critical objective to achieve ‘security pluralism’ in the Bay of Bengal region.

Analyzing upper ocean variability of the Chlorofluorocarbons in the Indian Ocean using regional high-resolution ocean biogeochemical modeling

A regional coupled ocean-biogeochemical modeling experiment is carried out over the Indian Ocean region (covering the Arabian Sea and Bay of Bengal) to generate high-resolution gridded data of Chlorofluorocarbons (CFC11 and CFC12) for the period 1999–2017. The results show that model realistically simulates hydrography of the region. It is found that western part of the Arabian Sea (AS) shows higher CFC concentration as compared to the eastern part. In the Bay of Bengal (BoB) region, the CFC decreases from north to south. The highest (lowest) surface CFC concentration in the AS and BoB is found in the winter (monsoon) season. The results indicate that while the near-surface CFC concentration of the BoB remains higher as compared to the AS, in the sub-surface (e.g., below 70–80 m depth), reverse is true. The AS region exhibits higher interannual CFC variability as compared to the BoB region. The CFC concentration over these regions decreases with time, albeit at a faster rate in the BoB region. The quantitative evaluation of the local inventories of CFC11 concentration is carried out in terms of penetration depth variability. The results indicate significant influence of ENSO on the CFC concentration of AS and BoB.

Impact of dust aerosols on the Indian Summer Monsoon Rainfall on intra-seasonal time-scale

The Indian subcontinent is a major hotspot of aerosol loading and several studies have demonstrated the importance of interaction between Asian dust aerosols and the Indian Summer Monsoon Rainfall (ISMR). However, a few studies have suggested a declining trend in the pre-monsoon dust loading over the Indian region. The present study investigates how the decrease in dust emissions influences the intensity of the monsoon rainfall over the Indian region using a fully coupled Weather Research and Forecasting model coupled with chemistry (WRF-Chem). We have conducted two sets of simulation experiments for the June-July-August-September (JJAS) season of 2017: (1) a control experiment with the default dust aerosol emissions, and (2) a sensitivity experiment by reducing dust emissions by 60%. Our analyses show that the reduction in dust emissions significantly alters the spatial distribution of seasonal mean monsoon rainfall with enhanced rainfall over the Bay of Bengal (BoB) and eastern coastal regions, and decreased rainfall over the lower Indo-Gangetic Plain (IGP), and parts of Central India (CI). It is found that the low aerosol loading conditions alter the large-scale circulation patterns along the tropical/sub-tropical region centred between 15°N and 35°N and 40°E −130°E, and through dynamical feedback, strengthens the convective rainfall over the BoB region. As a result, the 10–20 days sub-seasonal mode of the ISMR strengthens, facilitating enhanced westward propagation of rain-bearing systems formed over northern BoB which provides substantial rainfall over vast regions of the Indian subcontinent.

Genetic algorithm and deep learning models compared for swell wave height prediction

A comparative study has been conducted between genetic algorithm (GA) and deep learning models to predict swell wave heights in the Bay of Bengal (BOB) region. To simulate the required parameter SWAN (Simulating Waves Nearshore) model is integrated with daily 25 km wind from 2009 to 2018 for July and December separately representing the southwest and northeast monsoons respectively. For the BOB region empirical orthogonal function (EOF) analysis is applied on the swell parameter to study the spatial and temporal patterns. GA is applied on the principal component of swell wave heights to generate a forecast explicit equation and thus a basin scale EOF-GA model is established. Next a grid (200 N, 900E) is chosen in the head bay region and the outcomes of the standalone GA model and the deep learning models are compared to predict the time series data of swell wave heights (SWS). It is observed that the performances of the deep learning model is better during the calm conditions in December than the rough seas in July. Another grid (150 N, 820E) is chosen along the east coast through which the severe cyclonic storm PHETHAI (13–18 December 2018) passed and the model accuracies are tested. The EOF-GA model serves as an effective computationally cheap basin scale forecast model. Thus, both the genetic algorithm and deep learning models can be developed and utilized for normal and extreme wave prediction having wide application in the ocean engineering domains.

Prediction of Extremely Severe Cyclonic Storm “Fani” Using Moving Nested Domain

The prediction of extremely severe cyclonic storms has been a long-standing and challenging issue due to their short life period and large variation in intensities over a short time. In this study, we predict the track, intensity, and structure of an extremely severe cyclonic storm (ESCS) named ‘Fani,’ which developed over the Bay of Bengal region from 27 April to 4 May 2019, using the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) model. Two numerical experiments were conducted using the moving nested domain method with a 3 km horizontal resolution, one with the FLUX-1 air-sea flux parameterization scheme and the other with the FLUX-2 air-sea flux parameterization scheme. The NCEP operational Global Forecast System (GFS) analysis and forecast datasets with a 25 km horizontal resolution were used to derive the initial and boundary conditions. The WRF model’s predicted track and intensity were validated with the best-fit track dataset from the India Meteorological Department (IMD), and the structure was validated with different observations. The results showed that the WRF model with the FLUX-1 air-sea parameterization scheme accurately predicted the track, landfall (position and time), and intensity (minimum sea level pressure and maximum surface wind) of the storm. The track errors on days 1 to 4 were approximately 47 km, 123 km, 96 km, and 27 km in the FLUX-1 experiment and approximately 54 km, 142 km, 152 km, and 166 km in the FLUX-2 experiment, respectively. The intensity was better predicted in the FLUX-1 experiment during the first 60 h, while it was better predicted in the FLUX-2 experiment for the remaining period. The structure, in terms of relative humidity, water vapor, maximum reflectivity, and temperature anomaly of the storm, was also discussed and compared with available satellite and Doppler Weather Radar observations.

Distribution of cross-tropopause convection within the Asian monsoon region from May through October 2017

Abstract. We constructed a database of cross-tropopause convection in the Asian monsoon region for the months of May through October of 2017 using overshooting tops (OTs), deep convective features that penetrate the local cirrus anvil layer and the local tropopause, with Meteosat-8 geostationary satellite detections. The database of 40 918 OTs represents a hemispheric record of convection covering the study domain from 10∘ S to 55∘ N and from 40 to 115∘ E. With this database, we analyzed the geographic, monthly, and altitude distribution of this convection and compared it to the convective distributions represented by satellite observations of outgoing longwave radiation (OLR) and precipitation. We find that cross-tropopause convection is most active during the months of May through August (with daily averages of these months above 300 OTs per day) and declines through September and October. Most of this convection occurs within Northern India and Southern India, the Bay of Bengal, and the Indian Ocean regions, which together account for 75.1 % of all OTs. We further identify distinct, differing seasonal trends within the study subregions. For the Northern India, Southern India, and Bay of Bengal regions, the distribution of OTs follows the development of the Asian monsoon, with its north–south movement across the study period. This work demonstrates that when evaluating the effects of convection on lower stratospheric composition over the Asian monsoon region, it is important to consider the impact of cross-tropopause convection specifically, as well as the contributions from both land-based and oceanic regions due to the significant geographic and monthly variation in convective activity.

A Comparison of Wave Spectra during Pre-Monsoon and Post-Monsoon Tropical Cyclones under an Intense Positive IOD Year 2019

The impact of Indian Ocean Dipole (IOD) events on the generation and intensity of tropical cyclones under the influence of monsoons is explored. The standardized sea surface temperature (SST) anomalies are computed for the pre-monsoon and post-monsoon months for the Bay of Bengal (BOB) and Arabian Sea (AS) from 1971 to 2020 and relationships are analyzed with the frequency of tropical cyclones for the neutral, positive and negative IOD years. Ocean states are sensitive to cyclonic conditions exhibiting a complex spectral distribution of the wave energy. Due to a tropical cyclone, the surface waves remain under high wind forcing conditions for prolonged periods generating a huge amount of energy. The spectral wave model SWAN (Simulating WAves Nearshore) is used to generate the energy density spectra during FANI (26 April–5 May 2019), which was a pre-monsoon extreme severe cyclonic storm, and BULBUL (5–12 November 2019), which was a post-monsoon very severe cyclonic storm in the BOB region. This study aims to estimate the intensity of wave energy during tropical cyclones in the pre- and post-monsoon months for 2019 (an extremely positive IOD year).