Negative Indian Ocean Dipole Research Articles

Variations of phytoplankton chlorophyll in the Bay of Bengal: Impact of climate changes and nutrients from different sources

Phytoplankton biomass, quantified as the concentration of chlorophyll-a (CHL), is the base of the marine food web that supports fisheries production in the Bay of Bengal (BoB). Nutrients from river discharge, the ocean subsurface layer, and the atmosphere have been reported to determine CHL in the BoB. Which source of nutrients mainly determines CHL in different parts of the bay has not been determined. Furthermore, how climate variations influence nutrient inputs from different sources and their impacts on CHL have not been detailed. To address these questions, we used relationships between satellite-derived CHL and in situ river discharge data (a proxy for river-borne nutrients) from 1997 to 2016, physical variables, and modeled dust deposition (DD), a proxy for atmosphere-borne nutrients. Nutrients supplied from the ocean subsurface layer were assessed based on variations in physical parameters (i.e., wind stress curl, sea surface height anomaly, and sea surface temperature). We found that nutrients from the Ganges and Brahmaputra Rivers were important for CHL along the northern coast of the bay. By increasing rainfall and river discharge, La Niña extended high-CHL waters further southward. Nutrients from the ocean subsurface layer determine CHL variations mainly in the southwestern bay. We suggest that the variations in the supply of nutrients from the subsurface layer are related to the generation of mesoscale cyclonic eddies during La Niña, a negative Indian Ocean Dipole, or both. Climate-driven cyclonic eddies together with cyclones can intensify Ekman divergence and synergistically lead to a pronounced increase in CHL in the southwestern bay. Nutrients from the atmosphere mainly determine CHL in the central/eastern BoB. We further suggest that DD in the central/eastern BoB is influenced by ENSO with a 6–7-month time lag. CHL in the central/eastern bay responds to the ENSO 6–7 months after the ENSO peak because of the 6–7-month lag between ENSO and DD. This report provides valuable information needed to plan necessary actions for climate adaptation in local fisheries activities by elucidating how climate variations influence phytoplankton.

Bias correction of CMIP6 simulations of precipitation over Indian monsoon core region using deep learning algorithms

AbstractGeneral Circulation Models or Global Climate Models (GCMs) output consists of inevitable bias due to insufficient knowledge about parameterization schemes and other mathematical computations that involve thermodynamical and physical laws while designing climate models. Indian summer monsoon (southwest monsoon) accounts for 75%–90% of the annual rainfall over most climatic zones of India during the months, June, July, August, and September, which has a direct impact on the agricultural economy of India. The aim of this study is to bias correct the Coupled Model Intercomparison Project Phase – 6 (CMIP6) GCMs' precipitation data for the historical period from 1985 to 2014 and two Shared Socioeconomic Pathways (SSP) SSP1‐2.6 and SSP5‐8.5, from the period 2015 to 2100, with reference to the India Meteorological Department (IMD) observed rainfall gridded dataset. The datasets used are for the rain‐bearing Indian southwest monsoon season from the months, June to September. Monsoon Core Region is selected to carry out the bias correction using a couple of deep learning algorithms, namely one‐dimensional Convolutional Neural Network (CNN1D) and Long Short‐Term Memory Encoder‐Decoder (LSTM‐ED) Neural Network. The performance of both algorithms is evaluated with metrics. The LSTM‐ED algorithm yielded better results with least error output. The bias‐corrected data obtained using the LSTM‐ED algorithm is then compared with IMD observed rainfall data for the climatic events such as ENSO (El Niño and La Niña) and Positive and Negative IOD (Indian Ocean Dipole).

Long-Term Trend and Variability of Volume Transport and Advective Heat Flux through the Boundaries of the Java Sea Based on a Global Ocean Circulation Model (1950–2013)

The variability and trend of volume and advective heat flux, in addition to the net inflow and outflow of advective heat flux in the Java Sea for 64 years (1950–2013), along with its relationship with the monsoon, ENSO (El Niño Southern Oscillation), and IOD (Indian Ocean Dipole), have all been studied. A simulation of the 3D hydrodynamic HYCOM (HYbrid Coordinate Ocean Model) with a 1/8° grid resolution was performed in this study. Judging from the simulated results, the seasonal variability, which has a period of 12 months, has a very significant impact on contributing to the variability and trend of volume and advective heat flux, as well as the net inflow and outflow of advective heat flux in the Java Sea for 64 years. This is followed by interannual variability, which has a time range of 1.5–6.5 years, and interdecadal variability, with a period of 21.3–32 years. The interannual variability in the Java Sea is strongly caused by ENSO and IOD. El Niño and a positive IOD caused a weakening of southward transport through Karimata and the Bangka Strait. On the contrary, southward transport strengthened during La Niña and the negative IOD. Furthermore, La Niña and a positive IOD both strengthen (weaken) the transport westward (eastward) in the Sunda Strait (Eastern Java). On the other hand, El Niño and a negative IOD weaken (strengthen) the westward (eastward) transport in the Sunda Strait (Eastern Java). According to the findings, the IOD effect is stronger than the ENSO effect in the Java Sea. The inflow and outflow of volume transport in the Java Sea are in balance, but not the advective heat flux. The advective heat transported through Karimata and Bangka Strait to the Java Sea is up to 0.216 PW, while the total advective heat flux through the outflow straits (Sunda Strait and Eastern Java) is 0.220 PW. Thus, the net advective heat flux out of the Java Sea is 0.004 PW, allegedly obtained from an atmosphere–sea interaction in which the sea received heat from the atmosphere.

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).

El Nino/La Nina and IOD impact on Kharif season crops over western agro-climatic zones of India

Climate modes like ENSO (El Nino Southern Oscillation) and IOD (Indian Ocean Dipole) produce an impact on the monsoon rainfall over India. Monsoon rainfall is extremely important for the agriculture of our country. The impact of these climate modes on monsoon rainfall thus in turn affects the rain-fed crops (kharif). In this study, four kharif season crops namely rice (Oryza sativa), maize (Zea mays), pulses and sugarcane (Saccharum officinarum) are chosen over four arid/semi-arid agro-climatic zones of western India to study the effect of the climate modes on selected crops. The detailed analysis has been carried out to show the impact of rainfall in the El Nino/La Nina (phases of ENSO) and IOD years on the crop productions over the mentioned zones viz. (Central plateau and hills region; Western plateau and hills region; Gujarat hills and plains region; Western dry region) from 1966–2011. The results show that rice productions which require hot and humid conditions have been largely affected during drought years associated with El Nino which results in poor rainfall over all the zones. The production of pulses which does not require excess humid conditions shows marginal improvement during the neutral years or non-El Nino/non-La Nina years. Maize production seems to be better in La Nina years and worst in the El Nino years as La Nina years are responsible for good rainfall in all zones. El Nino years provide a minor impact on sugarcane productions in different zones. La Nina years are well suited for sugarcane production in all zones of our study as sugarcane requires a good amount of moisture. Positive IOD years are associated with poor crop productions as compared to negative IOD years mostly in all zones as most of the positive IOD years happen to be El Nino years. El Nino-rainfall relation being dominant than positive IOD-rainfall relation is, therefore, responsible for negative rainfall anomalies over the selected zones.

IMPACT PROFILE OF ENSO AND DIPOLE MODE ON RAINFALL AS ANTICIPATION OF HYDROMETEOROLOGICAL DISASTERS IN THE PROVINCE OF SOUTH SUMATRA

El Niño Southern Oscillation (ENSO) is a weather phenomenon in the Pacific Ocean. At the same time, Dipole Mode (DM) is an ocean-atmosphere interaction phenomenon in the Indian Ocean. The area of South Sumatra Province, which is in the Monsunal area, makes the influence of ENSO and DM very instrumental in determining the length of the rainy season and throughout the year. The South Sumatra region is very vulnerable to forest and land fire disasters due to the condition of the area in the form of swamps and peatlands, which are very easy to burn if the dry season occurs in the South Sumatra area. In this study, an analysis of the effect of ENSO and DM on rainfall in the South Sumatra Region from 1981 to 2020 was carried out using a simple linear regression method and the correlation coefficient using Niño 3.4 index data and Dipole Mode with rainfall data and consecutive rainy days data. Consecutive Wet Day (CWD). The purpose of this study was to determine the effect of Enso and Dipole Mode on rainfall and CWD in the South Sumatra Region. The results show that the correlation between ENSO and rainfall is 0.0017-0.002573, DM and rainfall is 0.05972, and ENSO and CWD is -0.068. The correlation between DMI and CWD is 0.513. So it can be said that ENSO and DMI have no effect on rainfall in the South Sumatra Province. Still, the amount of CWD in South Sumatra Province is significantly determined by the Dipole Mode Index (DMI) at a moderate level. The number of consecutive rainy days in South Sumatra Province is influenced by the dynamics of the ocean and atmosphere of the Indian Ocean, which is characterized by the presence of positive IOD and negative IOD phenomena.

Sea Surface Salinity Anomaly in the Bay of Bengal during the 2010 Extremely Negative IOD Event

Based on Soil Moisture and Ocean Salinity (SMOS) data and the Ocean Reanalysis System 5 (ORAS5) dataset, positive salinity anomalies exceeding 2 psu in the northern Bay of Bengal (BoB) and negative salinity anomalies with the peak of the freshening anomalies reaching −2 psu around Sri Lanka were observed in autumn 2010. Here, an analysis of the anomalous salt budget revealed that anomalous horizontal advection contributed most to the variability in salinity in the BoB. With the development of La Niña and negative Indian Ocean dipole (nIOD) in summer and autumn, the strong summer monsoon current and Wyrtki jet combined with the anomalous basin-scale cyclonic circulation led to more high-salinity water entering the northern BoB. In addition, more freshwater was transported southward along the eastern coast of India by east Indian coastal current (EICC) in autumn, resulting in extremely negative salinity anomalies around Sri Lanka and positive salinity anomalies in the northern BoB. Moreover, the freshwater around Sri Lanka was carried farther into the southeastern Arabian Sea by the west Indian coastal current (WICC) in November, which affected the salinity stratification in winter and then influenced the variation of the Arabian Sea Mini Warm Pool (ASMWP) in the following spring. The ASMWP could affect the Indian summer monsoon (ISM) through its influence on the monsoon onset vortex (MOV) over the southeast Arabian Sea (SEAS).

Leading-Mode Connections of the Interannual Variability in Upper-Ocean Salinity in the Tropical Indian Ocean

Abstract Leading modes of interannual variability in upper-ocean salinity in the tropical Indian Ocean (TIO) and their connections were studied based on 17 years (2002–18) of oceanic historical and reanalysis data. Empirical orthogonal function (EOF) analysis depicted the dominant roles of the first two leading modes in salinity variability in the TIO over a wide range of interannual time scales. Among the rich oscillations of the leading EOF modes, a coherent near-biennial band was identified with basinwide loading of sea surface salinity anomalies (SSSa) (EOF1) leading/lagging the northeast–southwest dipolar mode of SSSa (EOF2) by around 4 months across the TIO, with southwestward migration of SSSa center. The spatial loadings of the SSSa leading modes in the TIO were strongly shaped by sea surface temperature–related freshwater fluxes and wind-driven regional ocean circulation on a near-biennial time scale. Composite analysis of the mixed layer salinity budget reflected characteristic features of basin-scale ocean–atmosphere coupling, both temporally and regionally during the life cycle of the near-biennial fluctuation in anomalous salinity in the TIO. Consistent with the intrinsic oscillation paradigm in the observed Indian Ocean dipole (IOD) variation, the dynamic and thermodynamic feedbacks associated with switches from the positive to negative IOD modes provided the phase-connection mechanisms for the SSSa leading-mode displacement over the TIO. Significance Statement This study investigates the leading modes of interannual variability in upper-ocean salinity in the tropical Indian Ocean (TIO). The intrinsic oscillation and associated dynamic and thermodynamic feedbacks over the TIO drive the basinwide connections of upper-ocean salinity variability. Our results show that a coherent near-biennial band is identifiable within the leading modes of sea surface salinity anomalies (SSSa), in which the wind-induced horizontal advections and evaporation-minus-precipitation anomalies associated with the switches from positive to negative Indian Ocean dipole modes mainly provide the phase-transition mechanism of SSSa. This research illustrates substantial evidence for the displacement of basin-scale sea surface temperature anomalies modulating the structures of SSSa and inducing the dynamical connections of leading modes of SSSa on the near-biennial time scale.

Seasonal and Year-To-Year Variability of Boundary Currents and Eddy Salt Flux along the Eastern and Southern Coasts of Sri Lanka Observed by PIES and Satellite Measurements

Abstract Boundary currents along the Sri Lankan eastern and southern coasts serve as a pathway for salt exchange between the Bay of Bengal and the Arabian Sea basins in the northern Indian Ocean, which are characterized by their contrasting salinities. Measurements from two pairs of pressure-sensing inverted echo sounders (PIES) deployed along the Sri Lankan eastern and southern coasts as well as satellite measurements are used to understand the variability of these boundary currents and the associated salt transport. The volume transport in the surface (0–200-m depth) layer exhibits a seasonal cycle associated with the monsoonal wind reversal and interannual variability associated with the Indian Ocean dipole (IOD). In this layer, the boundary currents transport low-salinity water out of the Bay of Bengal during the northeast monsoon and transport high-salinity water into the Bay of Bengal during the fall monsoon transition of some years (e.g., 2015 and 2018). The Bay of Bengal salt input increases during the 2016 negative IOD as the eastward flow of high-salinity water during the fall monsoon transition intensifies, whereas the effect of the 2015/16 El Niño on the Bay of Bengal salt input is still unclear. The time-mean eddy salt flux over the upper 200 m estimated for the April 2015–March 2019 period along the eastern coast accounts for 9% of the salt budget required to balance an estimated 0.13 Sv (1 Sv ≡ 106 m3 s−1) of annual freshwater input into the Bay of Bengal. The time-mean eddy salt flux over the upper 200 m estimated for the December 2015–November 2019 period along the southern coast accounts for 27% of that same salt budget. Significance Statement In the northern Indian Ocean, the highly saline Arabian Sea undergoes extreme evaporation while the Bay of Bengal (BoB) receives excess freshwater input. The focus of this study is the role of the observed time-variable circulation around Sri Lanka that permits the exchange between these basins to maintain their salinity distributions. The circulation fluctuates seasonally following the monsoon wind reversal and interannually in response to large-scale climate modes. The BoB freshwater export around Sri Lanka occurs during the northeast monsoon, whereas saline water import occurs during the fall monsoon transition of some years. However, rapid changes in both water volume transport and salt exchange can occur. The circulation over 0–200-m depth transports ∼9%–27% of the BoB salt budget.

On the Predictability of the Extreme Drought in East Africa During the Short Rains Season

AbstractMany parts of East Africa experienced extremely dry conditions during the short rains season of October–December 2021. It was predicted a few months before by the ensemble seasonal prediction system based on the SINTEX‐F climate model. The analysis of co‐variability of inter‐member anomalies has revealed that the 2021 negative Indian Ocean Dipole was responsible for these unusually dry conditions over East Africa. We also show that a hybrid statistical‐dynamical framework is more skillful than the SINTEX‐F model at predicting drought in East Africa on longer lead time, which may help people to take necessary mitigation measures to reduce the devastating impact of the drought.

The influences of the Indian Ocean Dipole (IOD) on rainfall in South Aceh

This study aimed to examine the influences of the Indian Ocean Dipole (IOD) on rainfall in three districts in South Aceh. The analysis was undertaken using Dipole Mode Index (DMI) data and five years of rainfall (2016 to 2020) in West Labuhan Haji, Tapak Tuan, and Bakongan areas. This research employed a correlation analysis and the Principal Component Analysis, followed by Cluster Analysis to investigate the relationship between IOD and rainfall at the study location. The negative IOD occurred in 2016, and the positive IOD occurred in 2017, 2018, 2019, and 2020. The strongest positive DMI was in October 2019 (1.123˚C), while the strongest negative DMI was in July 2016 (0.661˚C). Generally, the sub-districts of West Labuhan Haji, Tapak Tuan, and Bakongan always have high rainfall. The highest rainfall in West Labuhan Haji was recorded in January 2017 (1014 mm/month), in Tapak Tuan in November 2017 (1073 mm/month), and in Bakongan in July 2020 (605 mm/month). The correlation between DMI and rainfall in the three locations shows different findings. Although it was very small, the IOD affected the rainfall in West Labuhan Haji, Tapak Tuan, and Bakongan. In West Labuhan Haji, the highest correlation was in lag 1 (0.188); in Tapak Tuan, the highest correlation was in lag 2 (0.156), while in Bakongan, the highest correlation was in lag 2 (-0.191). The correlations in these three locations are considered weak. Thus, the IOD is not the main factor affecting the rainfall in West Labuhan Haji, Tapak Tuan, and Bakongan. As South Aceh is located in windward, the orographic effect may influence high rainfall in this region.Keywords:DMIRainfallPrincipal component AnalysisWest Labuhan HajiTapak TuanBakongan

Asymmetric Response of Sea Surface Salinity to Extreme Positive and Negative Indian Ocean Dipole in the Southern Tropical Indian Ocean

AbstractBased on the Argo and multi‐satellite observations, this study investigates the asymmetric response of sea surface salinity (SSS) to two extreme positive and negative Indian Ocean Dipole (IOD) events in the southern tropical Indian Ocean (TIO). During positive IOD events, the easterly wind anomalies trigger zonal freshwater advection along the equator, decreasing SSS, while cold sea surface temperature (SST) depress the convective precipitation in the southeastern TIO (SETIO), increasing the SSS. Contrast SSS anomalies along the equator and in the SETIO show opposite phases during positive and negative IOD events. These SSS anomalies have enhanced in recent years, reaching the strongest in the extreme negative IOD in 2016 and positive IOD in 2019. The case study shows that positive SSS anomalies occurred in the southern TIO during both positive and negative IOD events in 2016 and 2019, suggesting significant asymmetry in SSS. Analysis of the mixed layer salinity budget shows that the local precipitation and the entrainment associated with the upwelling Rossby waves played an essential role in the SSS increase in 2016, while the decreased precipitation and horizontal advection caused by the westward South Equatorial Current contributed to the SSS increase in 2019. Further analyses suggest that SSS response is more sensitive to thermocline shoaling than deepening, and SSS response to precipitation is greater at shallower mixed layer than at deeper ones, which is the main reason for the asymmetric response of the SSS to negative and positive IOD events.

Objective determination of the winter monsoon onset dates and its interannual variability in Malaysia

AbstractThe northeast/winter monsoon over Malaysia often leads to extreme rainfall events and floods over the windward side of terrain due to the strong northeasterly winds. Comparatively, much less rain falls over the other are sheltered by the mountain ranges. Based on this consideration, the onset of monsoon in the region is best determined operationally using 925 hPa winds. Therefore, we propose the first, simple, single‐variable‐based method to determine the onset dates of winter monsoon is yet reliable and can be closely monitored for operational purposes. The onset date is defined in the third pentad when the average of three pentads of 925 hPa northerly wind speed is greater than 1 m·s−1, and at least one of three pentads must be greater than 2.5 m·s−1. The study also investigates the relationship between the interannual variability of onset date and El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). Late‐onset can be expected when La Niña develops in the boreal fall season. However, a similar association between monsoon onset and El Niño condition was not observed. The lead–lag correlation between the IOD and the onset dates shows that the onset is significantly negatively correlated with the IOD. During negative (positive) IOD events, a delay (early) onset is expected. Results also show that the relationship between the onset and IOD is more robust and linear than the ENSO.

Sea level extremes and compounding marine heatwaves in coastal Indonesia

Low-lying island nations like Indonesia are vulnerable to sea level Height EXtremes (HEXs). When compounded by marine heatwaves, HEXs have larger ecological and societal impact. Here we combine observations with model simulations, to investigate the HEXs and Compound Height-Heat Extremes (CHHEXs) along the Indian Ocean coast of Indonesia in recent decades. We find that anthropogenic sea level rise combined with decadal climate variability causes increased occurrence of HEXs during 2010–2017. Both HEXs and CHHEXs are driven by equatorial westerly and longshore northwesterly wind anomalies. For most HEXs, which occur during December-March, downwelling favorable northwest monsoon winds are enhanced but enhanced vertical mixing limits surface warming. For most CHHEXs, wind anomalies associated with a negative Indian Ocean Dipole (IOD) and co-occurring La Niña weaken the southeasterlies and cooling from coastal upwelling during May-June and November-December. Our findings emphasize the important interplay between anthropogenic warming and climate variability in affecting regional extremes.

Impact of Indian Ocean Dipole Events on Phytoplankton Size Classes Distribution in the Arabian Sea

Changes in the environmental condition associated with climatic events could potentially influence the PSC dynamics of the regional marine ecosystem. The Indian Ocean dipole (IOD) is one of the critical ocean–atmosphere interactions that affects the climate of the Arabian Sea, and it could be a potential factor influencing the regional PSC distribution. However, the relationship between PSC and IOD remains unclear and less explored. In this study, using the in-situ database acquired from the Arabian Sea, we reparametrized the three−component abundance−based phytoplankton size class model and applied it to reconstructed satellite−derived chlorophyll−a concentration to extract the fractional contribution of phytoplankton size classes to chlorophyll−a concentration. Further, we investigated the influence of IOD on the changes in the biological–physical properties in the Arabian Sea. The results showed that the biological–physical processes in the Arabian Sea are interlinked and the changes in the IOD mode control the physical variables like sea surface temperature (SST), sea surface height (SSH), and mixed layer depth (MLD), which influence the specific PSC abundance. Unprecedented changes in the PSC distribution and physical properties were observed during the extreme positive and negative IOD events, which clearly indicated the potential role of IOD in altering the PSC distribution in the Arabian Sea. This study highlights the impact of extreme climate events on PSC distribution and the need for a better understanding of the associated physical–biological–climate interactions.

Relating a Large‐Scale Variation of Waves in the Indian Ocean to the IOD

AbstractThis study used the ERA‐5 40‐year reanalysis data set from the European Centre for Medium‐Range Weather Forecasts to analyze the spatial characteristics of wind waves and swells in the Indian Ocean. Although swells from the Southern Ocean can propagate into the Bay of Bengal, the zonal surface Stokes drift has been shown to correlate well with wind waves. Investigation of the relationship between the Indian Ocean Dipole (IOD) and the surface Stokes drift revealed strong correlation in the tropical Indian Ocean. The surface Stokes drift plays a positive role in maintaining sea surface temperature stability by transporting more (less) abnormally cold water during periods of positive (negative) IOD events. The depth‐integrated wave transport is quantified by the spectra and bulk parameters, respectively. Although two methods provide estimates of the same order of magnitude, the transport value is larger when wave spectra are used. With this approach, the estimated wave transport is comparable to the Ekman transport and its zonal component is even greater for more than 80% of the sea areas in the Indian Ocean; thus, it would have substantial effect on sea surface temperature. This paper proposes a new idea for studying this climatic phenomenon by considering the large‐scale wave effect, which builds a bridge for energy transport between the eastern and western boundaries of the Indian Ocean.

Spatio-temporal signature of surface biophysical parameters in response to extreme IOD events using remote sensing

The Indian Ocean (IO) evidenced significant effects on regional and global ocean-atmospheric coupling variability in recent decades. Anomalous negative (positive) Indian Ocean Dipole (IOD) events witnessed along tropical IO during 2016 (2019) are one of them. The spatial signature of anomalous IOD events was studied using sea surface temperature anomaly (SSTA), sea surface height, sea surface salinity, chlorophyll-a, zonal and meridional wind components obtained from remote sensing data. The strong easterly wind anomaly blowing along the Sumatra coast causes strong coastal upwelling pioneer for the positive IOD event in 2019. The westward horizontal advection of seawater leads to low (high) sea surface height anomaly along eastern (western) tropical IO. The eastern (western) tropical IO becomes gradually cold (warm) during the mature phase (September–October–November) of positive IOD. Due to strong upwelling high and low sea surface salinity were observed along the eastern and western tropical IO respectively. The prolonged stronger upward (downward) Ekman pumping velocity in east (west) results in divergence (convergence) of seawater responsible for the increase (decrease) of chlorophyll-a and marine primary productivity. The reverse phenomena were characterized by warmer (cooler) SSTA, higher (lower) sea surface height, low (high) sea surface salinity, and decrease (increase) of chlorophyll-a in the eastern (western) tropical IO in the 2016 negative IOD year. The westward (eastward) zonal Ekman mass transport is possible fueling the extreme condition of positive (negative) IOD events. A strong eastward propagating downwelling Kelvin wave was observed due to the reflection of the upwelling Rossby wave from the African coast. Dominated picoplankton (microplankton) to other phytoplankton size classes are responsible for the reoccurrence of open ocean bloom along western (eastern) tropical IO during positive IOD.

Predictability of sea surface temperature anomalies at the eastern pole of the Indian Ocean Dipole—using a convolutional neural network model

In this study, we train a convolutional neural network (CNN) model using a selection of Coupled Model Intercomparison Project (CMIP) phase 5 and 6 models to investigate the predictability of the sea surface temperature (SST) variability off the Sumatra-Java coast in the tropical southeast Indian Ocean, the eastern pole of the Indian Ocean Dipole (IOD). Results show that the CNN model can beat the persistence of the interannual SST variability, such that the eastern IOD (EIOD) SST variability can be forecast up to 6 months in advance. Visualizing the CNN model using a gradient weighted class activation map shows that the strong positive IOD events (cold EIOD SST anomalies) can stem from different processes: internal Indian Ocean dynamics were associated with the 1994 positive IOD, teleconnection from the equatorial Pacific was important in 1997, and cooling off the Australian coast in the southeast Indian Ocean contributed to the 2019 positive IOD. The CNN model overcomes the winter prediction barrier of the IOD, to a large extent due to the frequent transition from a warm state of the Indian Ocean to a negative IOD condition (warm EIOD SST anomalies) over the boreal winter to the following spring period. The forecasting skills of the CNN model are on par with predictions from a coupled seasonal forecasting model (ACCESS-S2), even outperforming this dynamic model in seasons leading to the IOD peaks. The ability of the CNN model to identify key dynamic drivers of the EIOD SST variability suggests that the CMIP models can capture the internal Indian Ocean variability and its teleconnection with the Pacific climate variability.

Variability of Arabian Sea surface circulation and chlorophyll distribution: a remote sensing estimation

High resolution mean surface velocity field of the Arabian Sea was derived by combining sea level anomalies based on satellite altimetry data with the surface drifter data. The mean current field exhibits the western boundary Somali Current, weak westward North Equatorial Current, weak West Indian Coastal Current. Besides strong currents, the Arabian Sea exhibits strong mesoscale eddy activity in the western side. The seasonal surface circulation changes of the Arabian Sea and variability associated with the Indian Ocean Dipole (IOD) events were determined. The Somali Current is northward during summer, with a speed above 1.8 m/s in July and it reverses towards south in winter. Significant changes were found in the flow pattern during IOD events. An anticyclonic gyre near the equator was a conspicuous feature during the positive IOD. Further, the Great Whirl shows an earlier formation and dissipation during the positive IOD. Notably, a delay of southward reversal of the Somali Current is found during the positive IOD. The southward flow of West Indian Coastal Current during summer monsoon is much stronger during the positive IOD and the northward flow in fall is prominent during negative IOD. The eastward Equatorial Jet is absent in fall and instead an opposite (westward) flow prevails during the positive IOD. Enhanced Chl-a concentration occurs during the negative IOD, compared to the positive IOD, especially in the western Arabian Sea. The wind-driven upwelling and mesoscale eddies are significantly modifying the Chl-a distribution along the Somali Coast.

Interannual variability of internal tides in the Andaman Sea: an effect of Indian Ocean Dipole

A marginal sea in the north eastern Indian Ocean, the Andaman Sea, has been known for the presence of high-amplitude internal waves since the nineteenth century. In this study, we explored the interannual variations of the internal wave activity in this complex region. We found that the Dipole Mode Index, which represents the Indian Ocean Dipole (IOD), influences the circulation in the Andaman Sea, which in turn impacts its density stratification on interannual scales. Ocean Reanalysis System 5 data (1993–2018) is used to see an increasing trend in the sub-surface stratification, whereas it showed a decreasing trend in the near-surface waters. Numerical model simulations carried out from 2009 to 2018 have shown that the interannual variability in the generation of semidiurnal internal tides is governed by distinct parameters (tidal forcing and stratification) at different sites in different months. Enhanced upwelling (downwelling) is observed during positive (negative) IOD events. Sensitivity experiments conducted between extreme IOD events (2006 and 2016) revealed an increase in internal tide generation from positive IOD to negative IOD. Furthermore, a sharp decrease in local baroclinic dissipation is seen during negative IOD, increasing baroclinic flux into the Andaman Sea. An increase in the strength of positive IOD could lead to enhanced diapycnal mixing due to strong local dissipation, whereas an increase in the intensity of negative IOD could result in amplified propagation of internal waves.